CN115985455B - Data processing method suitable for medical big data cloud service platform - Google Patents
Data processing method suitable for medical big data cloud service platform Download PDFInfo
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Abstract
The invention provides a data processing method suitable for a medical big data cloud service platform, which is used for extracting medical information on a prescription form to obtain medical data information; invoking an electronic map, receiving a target position input by a user on the electronic map, generating a drug store searching area on the electronic map according to the current position, the target position and the initial angle of the user, and searching drug stores in the drug store searching area based on the type of purchased drugs to obtain alternative drug stores; combining the alternative drugstores according to the drug data information to obtain a purchasing drugstore set meeting purchasing conditions, and generating purchasing distances corresponding to the purchasing drugstore sets according to the purchasing drugstore sets, the current position and the target position; and acquiring the quantity of the drug stores corresponding to each purchasing drug store set, generating a recommendation coefficient corresponding to each purchasing drug store set according to the purchasing distance and the quantity of the drug stores, and acquiring the purchasing drug store set with the maximum recommendation coefficient as a reference drug store set to be recommended to a user.
Description
Technical Field
The invention relates to a data processing technology, in particular to a data processing method suitable for a medical big data cloud service platform.
Background
The medical informatization is an important component of population health informatization and medical industry development in China, and the medical resources in China are rich and comprise various medical big data, such as big data formed by Electronic Medical Records (EMR), radiological images, electronic prescriptions, test results, electronic Health Records (EHR) and the like. Among them, the medical prescription has important significance as a medication instruction issued for diagnosing, preventing or treating diseases for patients.
At present, for some patients who need to take medicines for a long time, because medicines and dosages of medicines which are prescribed by hospitals each time are limited, the patients may need to take medicines according to medical prescriptions prescribed by doctors at regular intervals, and one pharmacy may not necessarily have all medicines required by the patients or may not have all medicines required by the patients, at this time, the patients need to purchase the required medicines in a plurality of pharmacies, and the patients may spend more time purchasing the medicines, so that the efficacy of the purchasing medicines is low.
Therefore, how to automatically generate purchasing recommendation data in combination with the purchasing requirements of users and assist the users to rapidly and efficiently purchase required medicines becomes an urgent need to solve the problem.
Disclosure of Invention
The embodiment of the invention provides a data processing method suitable for a medical big data cloud service platform, which can automatically generate purchasing recommendation data in combination with the purchasing requirements of users and assist the users to rapidly and efficiently purchase required medicines.
In a first aspect of the embodiment of the present invention, a data processing method suitable for a medical big data cloud service platform is provided, including:
acquiring a prescription form uploaded by a user based on a user side, and extracting medicine information on the prescription form to obtain medicine data information, wherein the medicine data information comprises purchased medicine types and purchased medicine doses corresponding to the purchased medicine types;
invoking an electronic map, receiving a target position input by a user on the electronic map, generating a drug store searching area on the electronic map according to the current position, the target position and the initial angle of the user, and searching drug stores in the drug store searching area based on the purchased drug types to obtain alternative drug stores;
combining the alternative drug stores according to the drug data information to obtain a purchasing drug store set meeting purchasing conditions, and generating purchasing distances corresponding to each purchasing drug store set according to the purchasing drug store set, the current position and the target position;
And acquiring the quantity of the drug stores corresponding to each purchased drug store set, generating a recommendation coefficient corresponding to each purchased drug store set according to the purchase distance and the quantity of the drug stores, and acquiring the purchased drug store set with the maximum recommendation coefficient as a reference drug store set to be recommended to a user.
Optionally, in one possible implementation manner of the first aspect, the receiving the target location input by the user on the electronic map, generating a pharmacy searching area on the electronic map according to the current location, the target location and the initial angle of the user, searching the pharmacy in the pharmacy searching area based on the purchased medicine category, and obtaining the alternative pharmacy, including:
generating a straight line reference direction by taking the current position as a starting point and the target position as an end point;
determining a first region line positioned on a first side of the straight line reference direction and a second region line positioned on a second side of the straight line reference direction based on the starting point and the initial angle;
generating a pharmacy searching area according to the first area line and the second area line;
and acquiring a medicine list of each medicine shop in the medicine shop searching area, and taking the medicine shop with the purchased medicine type as an alternative medicine shop.
Optionally, in one possible implementation manner of the first aspect, the method further includes:
acquiring first medicine types corresponding to the purchased medicine types in medicine lists of alternative medicine stores and first medicine doses corresponding to the first medicine types;
if the first medicine type is less than the purchased medicine type and/or the first medicine dosage corresponding to the first medicine type is less than the purchased medicine dosage corresponding to the corresponding purchased medicine type, generating completion information;
acquiring the purchased medicine types lacking in the first medicine types based on the completion information, taking the purchased medicine types corresponding to which the first medicine doses are less than the corresponding purchased medicine doses as the completion medicine types, and acquiring the supplementary doses corresponding to the completion medicine types;
counting the number of the complement types corresponding to the complement drug types, generating an expansion angle according to the number of the complement types, and generating a complement search area on an electronic map according to the current position, the expansion angle, the first area line and the second area line;
acquiring a full medicine list of each pharmacy in the supplementary search area, and counting selected medicine types corresponding to the full medicine types in all the full medicine lists and selected doses corresponding to the selected medicine types;
And if the selected medicine type is still less than the full medicine type and/or the selected dosage corresponding to the selected medicine type is still less than the supplementary dosage corresponding to the corresponding full medicine type, repeating the steps until the selected medicine type meets the full medicine type and the selected dosage corresponding to the selected medicine type meets the supplementary dosage corresponding to the corresponding full medicine type, and stopping searching.
Optionally, in one possible implementation manner of the first aspect, counting a number of complement types corresponding to the complement drug types, and generating the expansion angle according to the number of complement types includes:
generating an angle adjustment coefficient according to the ratio of the number of the complement types to the number of the reference types, and adjusting an initial angle based on the angle adjustment coefficient to obtain an enlarged angle;
the expansion angle is calculated by the following calculation model,
wherein ,
to enlarge the angle->
To complement the number of species->
For the reference category number->
For the initial angle +.>
To expand the angle weight.
Optionally, in a possible implementation manner of the first aspect, generating a supplementary search area on the electronic map according to the current position, the expansion angle, the first area line and the second area line includes:
Determining a first supplemental line on a first side of the first region line and a second supplemental line on a second side of the second region line based on the current position and the expansion angle;
and generating a first supplementary search area according to the first area line and the first supplementary line, and generating a second supplementary search area according to the second area line and the second supplementary line.
Optionally, in one possible implementation manner of the first aspect, the method further includes:
receiving adjustment information of a user on the basis of the first supplement line or the second supplement line by the user side, obtaining an adjustment angle according to the adjustment information, and adjusting the area range of the supplement search area based on the adjustment angle;
the adjustment information is that a first supplement line is close to or far from the first area line, or a second supplement line is close to or far from the second area line, and an adjustment angle corresponding to the first supplement line is equal to an adjustment angle corresponding to the second supplement line.
Optionally, in one possible implementation manner of the first aspect, the method further includes:
if the adjustment angle is larger than the expansion angle, the adjustment angle is taken as an expansion angle, and if the adjustment angle is smaller than the expansion angle, the adjustment angle is taken as a contraction angle;
Counting the number of increases corresponding to the increasing angle and the number of decreases corresponding to the decreasing angle in a preset time period, adjusting the weight value of the increasing angle according to the number of increases and the number of decreases to obtain an adjusted weight value, and adjusting the calculation model based on the adjusted weight value;
the adjustment weight value is calculated by the following formula,
wherein ,
to increase the number of times->
To reduce the number of times->
For adjusting the weight value, +.>
To increase the normalized value +.>
To reduce the normalized value.
Optionally, in a possible implementation manner of the first aspect, combining the candidate drug stores according to the drug data information to obtain a purchasing drug store set includes:
acquiring first medicine types corresponding to the purchased medicine types in medicine lists of alternative medicine stores and first medicine doses corresponding to the first medicine types;
one or more alternative drug stores of which the first drug category meets the purchased drug category and the first drug dose meets the purchased drug dose of the corresponding purchased drug category are classified, and a purchased drug store set is obtained.
Optionally, in a possible implementation manner of the first aspect, generating a purchase distance corresponding to each purchase pharmacy set according to the purchase pharmacy set, the current location and the target location includes:
Acquiring purchasing positions corresponding to alternative drugstores in the purchasing drugstore set and purchasing distances corresponding to the current positions of the purchasing positions, and sequencing the alternative drugstores in the purchasing drugstore set in ascending order according to the purchasing distances to obtain a drugstore distance sequence;
acquiring a distance between a current position and a first alternative pharmacy in the pharmacy distance sequence based on an electronic map to obtain a first sub-distance, and acquiring a distance between adjacent alternative pharmacy in the pharmacy distance sequence to obtain a second sub-distance;
and obtaining the purchasing distance corresponding to the purchasing pharmacy set according to the first sub-distance and the plurality of second sub-distances.
Optionally, in one possible implementation manner of the first aspect, generating the recommendation coefficient corresponding to each purchased pharmacy set according to the purchase distance and the number of the pharmacy includes:
generating a first reference coefficient according to a basic purchasing distance and the purchasing distance, generating a second reference coefficient according to the basic number of drugstores and the number of drugstores, and generating a recommendation coefficient based on the first reference coefficient and the second reference coefficient;
the recommendation coefficient is calculated by the following formula,
wherein ,
for the recommended coefficient +. >
For benchmark purchasing distance, ++>
For purchasing distance->
For the first reference coefficient weight value, +.>
For the reference number of pharmacies>
For the number of pharmacies>
Is the second reference coefficient weight value.
The beneficial effects of the invention are as follows:
1. the invention can recommend the purchasing drug store set composed of the drug stores capable of purchasing all drugs on the prescription list for the user, and can assist the user to rapidly purchase the needed drugs. When the purchasing drugstore set is generated, a drugstore searching area is firstly generated according to the current position of the user, the target position input by the user and the initial angle, then the drugstores in the drugstore searching area are searched, and the drugstores with the types of medicines required by the prescription list in the area are used as alternative drugstores, so that the range of searching the drugstores can be reduced, the data processing amount of searching the drugstores is reduced, and the efficiency of searching the drugstores is improved. After the alternative drugstores are obtained, the invention also combines the alternative drugstores, so that a user can purchase all medicines on the prescription according to the combined drugstore sets, and the invention also calculates according to the purchase distance and the number of the drugstores corresponding to the combined drugstore sets, so as to obtain the recommendation coefficient corresponding to each drugstore set, and recommends the drugstore set with the highest recommendation coefficient to the user for reference, thereby assisting the user to purchase the required medicines quickly.
2. When the pharmacies in the pharmacist searching area can not buy all the medicines on the prescription, the invention also expands the searching range of the pharmacies to generate the corresponding supplementary searching area, and further searches the pharmacies in the area, so that the obtained alternative pharmacies can buy all the medicines required on the prescription, thereby correspondingly reducing the times of buying medicines by users. When the corresponding supplementary search area is generated, the corresponding expansion angle is generated according to the number corresponding to the medicine types needing to be complemented, the expanded area is used as the supplementary search area after the expansion angle is outwards expanded based on the medicine store search area, and the medicine stores in the area are further searched, so that the area range during supplementary search can be correspondingly adjusted according to the lacking medicine types, the efficiency of searching the medicine stores is improved, repeated searching of the medicine stores in the original medicine store search area is not needed, the data processing amount during further searching of the medicine stores can be reduced, and the efficiency of searching the medicine stores can be further improved.
3. The invention can also adjust the area range of the supplementary search area according to the use habits of different users, so that the search range in searching for a pharmacy can be more fit with the use habits of different users. When the method and the device are used for adjusting, firstly, adjustment information of the user for the supplementary search area in a preset time period is obtained, the adjustment information comprises information when the user increases or reduces the area range of the supplementary search area, statistics is carried out on the number of times of increasing or reducing the area range of the supplementary search area in the preset time period, the fact that the user is more prone to increasing or reducing the search area is judged according to the statistics result, corresponding increasing or reducing processing is carried out on the weight value corresponding to the expansion angle, and then the calculation model is adjusted according to the adjusted weight value, so that the expansion angle calculated by the calculation model can be more attached to the use habit of the user.
Drawings
Fig. 1 is a schematic diagram of a data processing method applicable to a medical big data cloud service platform according to an embodiment of the present invention;
FIG. 2 is a reference diagram of a search area according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a data processing system applicable to a medical big data cloud service platform according to an embodiment of the present invention;
fig. 4 is a schematic hardware structure of an electronic device according to an embodiment of the present invention.
Detailed Description
The invention is described in detail below with reference to the drawings and the specific embodiments.
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a schematic diagram of a data processing method suitable for a medical big data cloud service platform according to an embodiment of the present invention is shown, and an execution subject of the method shown in fig. 1 may be a software and/or hardware device. The execution bodies of the present application may include, but are not limited to, at least one of: user equipment, network equipment, etc. The user equipment may include, but is not limited to, computers, smart phones, personal digital assistants (Personal Digital Assistant, abbreviated as PDA), and the above-mentioned electronic devices. The network device may include, but is not limited to, a single network server, a server group of multiple network servers, or a cloud of a large number of computers or network servers based on cloud computing, where cloud computing is one of distributed computing, and a super virtual computer consisting of a group of loosely coupled computers. This embodiment is not limited thereto. The method comprises the steps S1 to S4, and specifically comprises the following steps:
S1, acquiring a prescription form uploaded by a user based on the user side, and extracting medicine information on the prescription form to obtain medicine data information, wherein the medicine data information comprises purchased medicine types and purchased medicine doses corresponding to the purchased medicine types.
In practical application, the prescription can be an electronic prescription, and when the medicine information on the prescription is extracted, the text content on the prescription can be identified, so that each medicine and the corresponding dosage of each medicine are obtained.
If the medicine prescribed by the doctor is a special medicine in a hospital, the medicine shop is not sold, and only a specific hospital can buy the medicine, and the medicine shop is not suitable for the scheme.
S2, calling the electronic map, receiving a target position input by a user on the electronic map, generating a drug store searching area on the electronic map according to the current position, the target position and the initial angle of the user, and searching for drug stores in the drug store searching area based on the purchased drug types to obtain alternative drug stores.
Further, after the types of medicines to be purchased and the dosages of each medicine to be purchased are obtained, the scheme can generate a medicine shop searching area for searching whether corresponding medicines are sold in medicine shops in the area, so that corresponding purchasing information is provided for users.
When the corresponding drugstore searching area is generated, a range can be generated according to the current position of the user, the destination which the user wants to go and the initial angle, the area in the range is used as the drugstore searching area, and corresponding searching is carried out on the drugstores in the area, so that the searching range of the drugstores can be reduced correspondingly, the searched drugstores are not far away from the current position and the destination of the user, and the time for the user to purchase in the drugstores is shortened.
Specifically, the specific implementation manner of step S2 may be:
s21, taking the current position as a starting point and the target position as an end point, and generating a straight line reference direction.
Referring to fig. 2, a reference diagram of a search area provided in an embodiment of the present invention is shown, where a point a may be a current position of a user, and a point B may be a target position input by the user, that is, a destination, and when a straight line reference direction is generated, the point a may be used as a starting point, and the point B may be used as an end point, so as to generate a corresponding straight line reference direction, that is, a virtual straight line connecting the point a and the point B in fig. 2.
S22, determining a first area line positioned at the first side of the straight line reference direction and a second area line positioned at the second side of the straight line reference direction based on the starting point and the initial angle, and generating a pharmacy searching area according to the first area line and the second area line.
The first side of the straight line reference direction may be a left side of the straight line reference direction, the second side of the straight line reference direction may be a right side of the straight line reference direction, and the initial angle may be a preset angle value.
As shown in fig. 2, a first area line located at the left side of the straight line reference direction, that is, a virtual straight line located at the left side of the straight line reference direction in fig. 2, and a second area line located at the right side of the straight line reference direction, that is, a virtual straight line located at the right side of the straight line reference direction in fig. 2, may be determined according to the starting point and the initial angle, and then a pharmacy search area, that is, a sector area formed by the first area line and the second area line in fig. 2, may be generated according to the first area line and the second area line.
S23, acquiring a medicine list of each medicine shop in the medicine shop searching area, and taking the medicine shop containing the purchased medicine type in the medicine list as an alternative medicine shop.
When searching for the drug stores in the drug store searching area, a drug list of drugs sold by each drug store can be acquired first, and then the drug store containing the drugs to be purchased is used as an alternative drug store.
For example, as shown in fig. 2, if two pharmacies containing medicines to be purchased, namely, a pharmacy C and a pharmacy D, are searched in the pharmacy search area, the two pharmacies may be used as candidate pharmacies.
In practice, since the pharmacy search area is limited in scope, there may be a case where the pharmacy in the pharmacy search area cannot purchase all medicines on the order.
Therefore, the invention further comprises the following schemes based on the scheme:
s24, obtaining first medicine types corresponding to the purchased medicine types and first medicine doses corresponding to the first medicine types in the medicine list of each candidate medicine store.
First, the solution can obtain the medicines on the prescription list available in each alternative pharmacy, and the corresponding stock quantity, namely the first medicine types and the first medicine doses corresponding to each first medicine type.
S25, if the first medicine type is less than the purchased medicine type and/or the first medicine dosage corresponding to the first medicine type is less than the purchased medicine dosage corresponding to the corresponding purchased medicine type, generating the completion information.
Second, if all of the required purchased medicines are not available at all of the alternative pharmacies and/or the required purchased medicines are out of stock, the solution generates corresponding replenishment information.
S26, acquiring the purchased medicine types lacking in the first medicine types based on the completion information, taking the purchased medicine types corresponding to which the first medicine doses are smaller than the corresponding purchased medicine doses as the completion medicine types, and acquiring the supplementary doses corresponding to the completion medicine types.
Then, the scheme can obtain the types of medicines to be complemented and the corresponding medicine dosages, namely the types of the complemented medicines and the corresponding supplementary dosages of the types of the complemented medicines according to the complement information.
It will be appreciated that the medicines to be replenished include medicines lacking in kind and medicines lacking in dosage, and therefore, the scheme can correspondingly replenish the medicines to be replenished under both conditions as the types of medicines to be replenished.
And S27, counting the number of the complement types corresponding to the complement drug types, generating an expansion angle according to the number of the complement types, and generating a complement search area on an electronic map according to the current position, the expansion angle, the first area line and the second area line.
Further, after the types of the completed medicines are obtained, the scheme can generate corresponding expansion angles according to the types and the numbers of the types of the completed medicines, and further search corresponding drugstores in the area formed by the expansion angles.
In some embodiments, the expansion angle may be obtained by:
and generating an angle adjustment coefficient according to the ratio of the number of the complement types to the number of the reference types, and adjusting the initial angle based on the angle adjustment coefficient to obtain an enlarged angle.
It will be appreciated that the more types of medicines that need to be replenished, the more medicines that are missing will be described, so that the range of the area to be searched can be adjusted according to the expansion angle generated by the types of medicines that need to be replenished during searching.
The expansion angle is calculated by the following calculation model,
wherein ,
to enlarge the angle->
To complement the number of species->
For the reference category number->
For the initial angle +.>
To expand the angle weight.
From the above formula, it can be seen that the number of the complement species
The larger the indication, the more medicine is missing, and therefore the angle +.>
The method can also correspondingly increase the search area, so that the more the searched drugstores meeting the requirements are, and the efficiency in searching can be improved.
After the expansion angle is obtained, the scheme also generates a corresponding supplementary search area based on the following steps:
a first supplemental line on a first side of the first region line and a second supplemental line on a second side of the second region line are determined based on the current position and the expansion angle.
As shown in fig. 2, in determining the supplementary search area, an imaginary straight line located at the left side of the first area line may be determined as a first supplementary line, and an imaginary straight line located at the right side of the second area line may be determined as a second supplementary line.
And generating a first supplementary search area according to the first area line and the first supplementary line, and generating a second supplementary search area according to the second area line and the second supplementary line.
And then generating a first supplementary search area according to the first area line and the first supplementary line, namely a sector area positioned at the left side of the pharmacy search area in fig. 2, and generating a second supplementary search area according to the second area line and the second supplementary line, namely a sector area positioned at the right side of the pharmacy search area in fig. 2.
In addition, on the basis of the scheme, the invention further comprises the following scheme:
a1, receiving adjustment information of a user on the basis of the first supplement line or the second supplement line, obtaining an adjustment angle according to the adjustment information, and adjusting the area range of the supplement search area based on the adjustment angle.
It will be appreciated that since each user searches for a pharmacy with different search habits, some users may prefer a large scale search and some users may prefer a small scale search, and thus may be adjusted based on the user's usage habits after the supplemental search area is obtained.
Specifically, the area range of the supplementary search area may be adjusted according to the adjustment of the first supplementary line or the second supplementary line by the user.
A2, wherein the adjustment information is that a first supplement line is close to or far from the first area line, or a second supplement line is close to or far from the second area line, and an adjustment angle corresponding to the first supplement line is equal to an adjustment angle corresponding to the second supplement line.
When the first supplementary line is close to the first region line, the adjustment angle is smaller than the expansion angle, which means that the region range of the supplementary search region is reduced by the user at this time.
When the first supplementary line is far from the first area line, the adjustment angle is larger than the expansion angle, which means that the area range of the supplementary search area is increased by the user.
Furthermore, the scheme adjusts the calculation model according to the use habit of the user, and comprises the following specific steps:
And if the adjustment angle is larger than the expansion angle, the adjustment angle is taken as an expansion angle, and if the adjustment angle is smaller than the expansion angle, the adjustment angle is taken as a contraction angle.
Counting the number of increases corresponding to the increasing angle and the number of decreases corresponding to the decreasing angle in a preset time period, adjusting the weight value of the increasing angle according to the number of increases and the number of decreases to obtain an adjusted weight value, and adjusting the calculation model based on the adjusted weight value.
It will be appreciated that the more the number of increases within the preset time period, the more the user may prefer to search for an expanded range of the pharmacy, and the more the number of decreases within the preset time period, the more the user may prefer to search for a contracted range of the pharmacy, so that the expansion angle weight value may be adjusted according to the number of increases and decreases, and the calculation model may be adjusted.
Specifically, the adjustment weight value may be calculated by the following formula,
wherein ,
to increase the number of times->
To reduce the number of times->
For adjusting the weight value, +.>
To increase the normalized value +.>
To reduce the normalized value.
As can be seen from the above formula, when the number of times is increased
Greater than the reduction number->
At this time, it is explained that the user may be more inclined to search for an expanded range of the pharmacy within the preset period of time, and thus the expanded angle weight value +.>
When the adjustment is performed, the expansion processing can be performed on the image so that the expansion angle can be performed on the image when the expansion angle is calculated next time according to the calculation model, thereby expanding the area range when the search is supplemented. />
When the number of times is increased
Less than the reduction number +.>
At this time, it is explained that the user may be more inclined to search for a reduced range of the pharmacy within the preset period of time, and thus +.>
When the adjustment is performed, the expansion angle can be reduced, so that the expansion angle can be reduced when calculated according to the calculation model next time, and the area range during the supplementary search is reduced.
By the method, the supplement range of the drug store can be adjusted according to the use habit of the user, so that the search range of the drug store can be more fit with the use habit of different users.
S28, acquiring a full medicine list of each pharmacy in the supplementary search area, and counting selected medicine types corresponding to the full medicine types in all the full medicine lists and selected doses corresponding to the selected medicine types.
After generating the corresponding supplementary search area based on the expansion angle, the scheme can further search the drugstores in the search area to see whether the drugstores in the area can buy the totally absent medicine.
For example, as shown in fig. 2, if the pharmacy E and the pharmacy F are searched in the expanded search area, the solution further searches for the medicines in the pharmacy E and the pharmacy F to see if the medicines can be purchased in the whole missing medicines.
Specifically, the scheme can compare the inventory of the drug store in the supplementary search area with the missing drugs, so that the missing drug types and the corresponding drug doses in the drug store in the area are obtained, namely the selected drug types and the corresponding selected doses.
And S29, if the selected medicine type is still less than the full medicine type and/or the selected dosage corresponding to the selected medicine type is still less than the supplementary dosage corresponding to the corresponding full medicine type, repeating the steps until the selected medicine type meets the full medicine type and the selected dosage corresponding to the selected medicine type meets the supplementary dosage corresponding to the corresponding full medicine type, and stopping searching.
If the required medicine cannot be purchased in the pharmacy in the supplementary search area, the scheme also repeats the step of expanding the search until the required medicine can be purchased.
By the method, the range of searching for the drug store can be correspondingly reduced, the data processing amount during searching for the drug store is reduced, and the efficiency during searching for the drug store is improved.
And S3, combining the alternative drug stores according to the drug data information to obtain a purchasing drug store set meeting purchasing conditions, and generating purchasing distances corresponding to all the purchasing drug store sets according to the purchasing drug store set, the current position and the target position.
In practical application, because the medicine stock of each pharmacy is different, the situation that one pharmacy cannot purchase all medicines on the prescription list can occur, and therefore, the invention can also combine alternative pharmacies, so that the combined pharmacy set can purchase all medicines required to be purchased.
Specifically, in some embodiments, the purchasing pharmacy set may be obtained through steps S31 to S32, which is specifically as follows:
s31, obtaining first medicine types corresponding to the purchased medicine types and first medicine doses corresponding to the first medicine types in medicine lists of candidate medicine stores.
Similarly, when the purchasing drug store set is obtained, the scheme can also obtain the drugs on the purchasable prescription list in each alternative drug store and the corresponding stock quantity.
S32, classifying one or more alternative drugstores of which the first medicine category meets the purchasing medicine category and the first medicine dosage meets the purchasing medicine dosage of the corresponding purchasing medicine category, and obtaining a purchasing drugstore set.
When the scheme is combined, drug stores meeting the requirement of drug category purchase and corresponding dosage meeting the condition are combined together to generate corresponding purchase drug store sets.
For example, if pharmacy A is able to purchase all of the drugs on the prescription and the corresponding drug inventory also meets the drug dose on the prescription, a corresponding set of purchasing pharmacy may be generated from pharmacy A. Or if the two pharmacies of pharmacies a and B add up to purchase all of the drugs on the full prescription and the corresponding drug inventory also meets the drug dose on the prescription, then a corresponding set of purchasing pharmacies may be generated from pharmacies a and B.
It can be understood that after the corresponding purchasing drug store sets are generated, the corresponding purchasing distance is obtained, and the distance of the purchasing drug store according to each purchasing drug store set is determined according to the corresponding purchasing distance.
Specifically, in other embodiments, the purchasing distance corresponding to each purchasing pharmacy set may be obtained through steps S33 to S34, which is specifically as follows:
s33, acquiring purchasing positions corresponding to the alternative drugstores in the purchasing drugstore set and purchasing distances corresponding to the current positions of the purchasing positions, and sorting the alternative drugstores in the purchasing drugstore set in ascending order according to the purchasing distances to obtain a drugstore distance sequence.
In practical application, the purchasing position corresponding to each candidate drug store and the purchasing distance between the current position of the user and the purchasing position of each candidate drug store can be obtained according to the electronic map.
S34, obtaining a first sub-distance based on the electronic map and the distance between the current position and the first alternative pharmacy in the pharmacy distance sequence, and obtaining a second sub-distance based on the distance between the adjacent alternative pharmacy in the pharmacy distance sequence.
And S35, obtaining the purchasing distance corresponding to the purchasing pharmacy set according to the first sub-distance and the plurality of second sub-distances.
For example, as shown in fig. 2, if point a is the current location of the user, and point C and point D are the purchase locations corresponding to the candidate drug stores in the purchase drug store set, when generating the purchase distance corresponding to the purchase drug store set, the distance between point a and point C may be obtained first, then the distance between point C and point D may be obtained, and then all the obtained distances may be added to obtain the corresponding purchase distance.
By the method, the purchasing drug store sets capable of purchasing all the drugs on the prescription list and the corresponding purchasing distance of each purchasing drug store set can be obtained, so that a user can purchase all the drugs on the prescription list according to the purchasing drug store sets.
S4, acquiring the quantity of the drug stores corresponding to each purchased drug store set, generating a recommendation coefficient corresponding to each purchased drug store set according to the purchase distance and the quantity of the drug stores, and acquiring the purchased drug store set with the maximum recommendation coefficient as a reference drug store set to be recommended to a user.
Further, after obtaining the purchase drug store sets and the purchase distances corresponding to each purchase drug store set, the invention also obtains the number of drug stores corresponding to each purchase drug store set, generates a recommendation coefficient through the purchase distances and the number of drug stores, and recommends the purchase drug store set with the largest recommendation coefficient to a user for purchase reference.
The specific implementation manner of step S4 based on the above embodiment may be:
s41, generating a first reference coefficient according to the standard purchasing distance and the purchasing distance, generating a second reference coefficient according to the standard number of drugstores and the number of drugstores, and generating a recommendation coefficient based on the first reference coefficient and the second reference coefficient.
It will be appreciated that the user may generally be affected by both distance and number of pharmacies to be accessed during purchase, and thus may calculate the corresponding recommendation coefficients based on the two dimensions of data.
The recommendation coefficient is calculated by the following formula,
wherein ,
for the recommended coefficient +.>
For benchmark purchasing distance, ++>
For purchasing distance->
For the first reference coefficient weight value, +.>
For the reference number of pharmacies>
For the number of pharmacies>
Is the second reference coefficient weight value.
From the above formula, the purchasing distance
The larger the distance the user needs to travel to make a purchase, the longer the time the user spends making a purchase, and the lower the efficiency of the purchase, so when the purchase distance +.>
The larger the corresponding recommendation coefficient +.>
The smaller may be set, thereby reducing the probability of recommending its corresponding set of purchased pharmacies to the user and vice versa.
Quantity of drugstore
The larger the pharmacy that the user needs to go to when making a purchase, the longer the time he spends at the time of purchase, and the lower the efficiency of purchase, so when the number of pharmacy is +. >
The larger the corresponding recommendation coefficient +.>
The smaller may also be set, thereby reducing the probability of recommending its corresponding set of purchased pharmacies to the user, and vice versa.
By the method, a more preferable purchasing pharmacy set can be recommended to the user, so that the user is assisted in buying the required medicines quickly.
Referring to fig. 3, a schematic structural diagram of a data processing system suitable for a medical big data cloud service platform according to an embodiment of the present invention includes:
the extraction module is used for acquiring a prescription form uploaded by a user based on a user side, extracting the medicine information on the prescription form and obtaining medicine data information, wherein the medicine data information comprises purchased medicine types and purchased medicine doses corresponding to the purchased medicine types;
the candidate module is used for calling the electronic map, receiving a target position input by a user on the electronic map, generating a drug store searching area on the electronic map according to the current position, the target position and the initial angle of the user, and searching drug stores in the drug store searching area based on the purchased drug types to obtain candidate drug stores;
The completion module is used for combining the alternative drugstores according to the medicine data information to obtain a purchasing drugstore set meeting purchasing conditions, and generating purchasing distances corresponding to the purchasing drugstore sets according to the purchasing drugstore set, the current position and the target position;
and the recommending module is used for acquiring the quantity of the drug stores corresponding to each purchased drug store set, generating a recommending coefficient corresponding to each purchased drug store set according to the purchasing distance and the quantity of the drug stores, and acquiring the purchased drug store set with the largest recommending coefficient as a reference drug store set to be recommended to a user.
The apparatus of the embodiment shown in fig. 3 may be correspondingly used to perform the steps in the embodiment of the method shown in fig. 1, and the implementation principle and technical effects are similar, and are not repeated here.
Referring to fig. 4, a schematic hardware structure of an electronic device according to an embodiment of the present invention is shown, where the electronic device 40 includes: a processor 41, a memory 42 and a computer program; wherein the method comprises the steps of
A memory 42 for storing the computer program, which may also be a flash memory (flash). Such as application programs, functional modules, etc. implementing the methods described above.
A processor 41 for executing the computer program stored in the memory to implement the steps executed by the apparatus in the above method. Reference may be made in particular to the description of the embodiments of the method described above.
Alternatively, the memory 42 may be separate or integrated with the processor 41.
When the memory 42 is a device separate from the processor 41, the apparatus may further include:
a bus 43 for connecting the memory 42 and the processor 41.
The present invention also provides a readable storage medium having stored therein a computer program for implementing the methods provided by the various embodiments described above when executed by a processor.
The readable storage medium may be a computer storage medium or a communication medium. Communication media includes any medium that facilitates transfer of a computer program from one place to another. Computer storage media can be any available media that can be accessed by a general purpose or special purpose computer. For example, a readable storage medium is coupled to the processor such that the processor can read information from, and write information to, the readable storage medium. In the alternative, the readable storage medium may be integral to the processor. The processor and the readable storage medium may reside in an application specific integrated circuit (Application Specific Integrated Circuits, ASIC for short). In addition, the ASIC may reside in a user device. The processor and the readable storage medium may reside as discrete components in a communication device. The readable storage medium may be read-only memory (ROM), random-access memory (RAM), CD-ROMs, magnetic tape, floppy disk, optical data storage device, etc.
The present invention also provides a program product comprising execution instructions stored in a readable storage medium. The at least one processor of the device may read the execution instructions from the readable storage medium, the execution instructions being executed by the at least one processor to cause the device to implement the methods provided by the various embodiments described above.
In the above embodiment of the apparatus, it should be understood that the processor may be a central processing unit (english: central Processing Unit, abbreviated as CPU), or may be other general purpose processors, digital signal processors (english: digitalSignal Processor, abbreviated as DSP), application specific integrated circuits (english: application Specific Integrated Circuit, abbreviated as ASIC), or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor for execution, or in a combination of hardware and software modules in a processor for execution.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
Claims (8)
1. The data processing method suitable for the medical big data cloud service platform is characterized by comprising the following steps of:
acquiring a prescription form uploaded by a user based on a user side, and extracting medicine information on the prescription form to obtain medicine data information, wherein the medicine data information comprises purchased medicine types and purchased medicine doses corresponding to the purchased medicine types;
invoking an electronic map, receiving a target position input by a user on the electronic map, generating a drug store searching area on the electronic map according to the current position, the target position and the initial angle of the user, and searching drug stores in the drug store searching area based on the purchased drug types to obtain alternative drug stores;
combining the alternative drug stores according to the drug data information to obtain a purchasing drug store set meeting purchasing conditions, and generating purchasing distances corresponding to each purchasing drug store set according to the purchasing drug store set, the current position and the target position;
acquiring the quantity of the drug stores corresponding to each purchased drug store set, generating a recommendation coefficient corresponding to each purchased drug store set according to the purchase distance and the quantity of the drug stores, and acquiring the purchased drug store set with the maximum recommendation coefficient as a reference drug store set to be recommended to a user;
Receiving a target position input by a user on an electronic map, generating a drug store searching area on the electronic map according to the current position, the target position and an initial angle of the user, searching drug stores in the drug store searching area based on the purchased drug types to obtain alternative drug stores, and comprising the following steps:
generating a straight line reference direction by taking the current position as a starting point and the target position as an end point;
determining a first region line positioned on a first side of the straight line reference direction and a second region line positioned on a second side of the straight line reference direction based on the starting point and the initial angle;
generating a pharmacy searching area according to the first area line and the second area line;
acquiring a medicine list of each medicine shop in a medicine shop searching area, and taking the medicine shop containing the purchased medicine type in the medicine list as an alternative medicine shop;
acquiring first medicine types corresponding to the purchased medicine types in medicine lists of alternative medicine stores and first medicine doses corresponding to the first medicine types;
if the first medicine type is less than the purchased medicine type and/or the first medicine dosage corresponding to the first medicine type is less than the purchased medicine dosage corresponding to the corresponding purchased medicine type, generating completion information;
Acquiring the purchased medicine types lacking in the first medicine types based on the completion information, taking the purchased medicine types corresponding to which the first medicine doses are less than the corresponding purchased medicine doses as the completion medicine types, and acquiring the supplementary doses corresponding to the completion medicine types;
counting the number of the complement types corresponding to the complement drug types, generating an expansion angle according to the number of the complement types, and generating a complement search area on an electronic map according to the current position, the expansion angle, the first area line and the second area line;
acquiring a full medicine list of each pharmacy in the supplementary search area, and counting selected medicine types corresponding to the full medicine types in all the full medicine lists and selected doses corresponding to the selected medicine types;
and if the selected medicine type is still less than the full medicine type and/or the selected dosage corresponding to the selected medicine type is still less than the supplementary dosage corresponding to the corresponding full medicine type, repeating the steps until the selected medicine type meets the full medicine type and the selected dosage corresponding to the selected medicine type meets the supplementary dosage corresponding to the corresponding full medicine type, and stopping searching.
2. The method of claim 1, wherein the step of determining the position of the substrate comprises,
counting the number of the complement types corresponding to the complement drug types, generating an expansion angle according to the number of the complement types, including:
generating an angle adjustment coefficient according to the ratio of the number of the complement types to the number of the reference types, and adjusting an initial angle based on the angle adjustment coefficient to obtain an enlarged angle;
the expansion angle is calculated by the following calculation model,
wherein ,
to enlarge the angle->
To complement the number of species->
For the reference category number->
For the initial angle of the beam,
to expand the angle weight.
3. The method of claim 2, wherein the step of determining the position of the substrate comprises,
generating a supplementary search area on the electronic map according to the current position, the expansion angle, the first area line and the second area line, including:
determining a first supplemental line on a first side of the first region line and a second supplemental line on a second side of the second region line based on the current position and the expansion angle;
and generating a first supplementary search area according to the first area line and the first supplementary line, and generating a second supplementary search area according to the second area line and the second supplementary line.
4. A method according to claim 3, further comprising:
receiving adjustment information of a user on the basis of the first supplement line or the second supplement line by the user side, obtaining an adjustment angle according to the adjustment information, and adjusting the area range of the supplement search area based on the adjustment angle;
the adjustment information is that a first supplement line is close to or far from the first area line, or a second supplement line is close to or far from the second area line, and an adjustment angle corresponding to the first supplement line is equal to an adjustment angle corresponding to the second supplement line.
5. The method as recited in claim 4, further comprising:
if the adjustment angle is larger than the expansion angle, the adjustment angle is taken as an expansion angle, and if the adjustment angle is smaller than the expansion angle, the adjustment angle is taken as a contraction angle;
counting the number of increases corresponding to the increasing angle and the number of decreases corresponding to the decreasing angle in a preset time period, adjusting the weight value of the increasing angle according to the number of increases and the number of decreases to obtain an adjusted weight value, and adjusting the calculation model based on the adjusted weight value;
The adjustment weight value is calculated by the following formula,
wherein ,
to increase the number of times->
To reduce the number of times->
For adjusting the weight value, +.>
To increase the normalized value +.>
To reduce the normalized value.
6. The method of claim 1, wherein the step of determining the position of the substrate comprises,
combining the alternative drugstores according to the drug data information to obtain a purchasing drugstore set, wherein the purchasing drugstore set comprises:
acquiring first medicine types corresponding to the purchased medicine types in medicine lists of alternative medicine stores and first medicine doses corresponding to the first medicine types;
one or more alternative drug stores of which the first drug category meets the purchased drug category and the first drug dose meets the purchased drug dose of the corresponding purchased drug category are classified, and a purchased drug store set is obtained.
7. The method of claim 6, wherein the step of providing the first layer comprises,
generating a purchase distance corresponding to each purchase pharmacy set according to the purchase pharmacy set, the current position and the target position, wherein the purchase distance comprises the following steps:
acquiring purchasing positions corresponding to alternative drugstores in the purchasing drugstore set and purchasing distances corresponding to the current positions of the purchasing positions, and sequencing the alternative drugstores in the purchasing drugstore set in ascending order according to the purchasing distances to obtain a drugstore distance sequence;
Acquiring a distance between a current position and a first alternative pharmacy in the pharmacy distance sequence based on an electronic map to obtain a first sub-distance, and acquiring a distance between adjacent alternative pharmacy in the pharmacy distance sequence to obtain a second sub-distance;
and obtaining the purchasing distance corresponding to the purchasing pharmacy set according to the first sub-distance and the plurality of second sub-distances.
8. The method of claim 7, wherein the step of determining the position of the probe is performed,
generating recommendation coefficients corresponding to each purchasing pharmacy set according to the purchasing distance and the pharmacy number, wherein the recommendation coefficients comprise:
generating a first reference coefficient according to a basic purchasing distance and the purchasing distance, generating a second reference coefficient according to the basic number of drugstores and the number of drugstores, and generating a recommendation coefficient based on the first reference coefficient and the second reference coefficient;
the coefficients are recommended by the following formula,
wherein ,
for the recommended coefficient +.>
For benchmark purchasing distance, ++>
For purchasing distance->
For the first reference coefficient weight value, +.>
For the reference number of pharmacies>
For the number of pharmacies>
Is the second reference coefficient weight value. />
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