CN115206548A - Intelligent inquiry and queuing inspection system for outpatient service - Google Patents

Intelligent inquiry and queuing inspection system for outpatient service Download PDF

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CN115206548A
CN115206548A CN202210858528.7A CN202210858528A CN115206548A CN 115206548 A CN115206548 A CN 115206548A CN 202210858528 A CN202210858528 A CN 202210858528A CN 115206548 A CN115206548 A CN 115206548A
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叶娟
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Sichuan Huhui Software Co ltd
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    • G—PHYSICS
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    • G16H80/00—ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/20—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/20—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms

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Abstract

An outpatient intelligent inquiry and queuing inspection system comprising: a program, a man-machine interaction device and a mobile phone terminal; the method comprises the following specific steps: the method comprises the following steps that firstly, a three-dimensional camera array is adopted to collect diagnosis images of doctors, details of specific cases are in one-to-one correspondence, and a case library D is generated; establishing a three-dimensional human body model at a server, and establishing a one-to-one mapping relation between the position of the three-dimensional human body model and a medical knowledge map; step two, mapping the language and the behavior language of the patient into the disease condition position of the three-dimensional human body model; thirdly, forming an original diagnosis, comparing the disease case library D, correcting the original diagnosis to form a primary diagnosis report, recommending examination items, and judging and confirming the primary diagnosis report and the recommended examination items by a doctor; fourthly, a queuing optimization algorithm is adopted for the inspection items to form inspection navigation; and step five, sending the examination navigation to a mobile phone APP of the patient, queuing in sequence to complete the examination, and optimizing medical logic by combining examination conclusions.

Description

Intelligent inquiry and queuing inspection system for outpatient service
Technical Field
The invention relates to the technical field of intelligent inquiry and queuing, in particular to an intelligent inquiry and queuing inspection system for outpatient service.
Background
Aiming at the problems that when a patient goes to a hospital outpatient service, various medical examinations are often needed for the patient to be clear of the condition of the patient and for doctors to perform better treatment. For example: the diabetes patient needs to be checked for the indexes such as blood drawing, sugar test, fasting blood sugar, liver and kidney functions, blood fat, ions, islet functions and the like; secondly, the examination of indexes such as fundus photography, electromyography, arterial ultrasound, urine microalbumin determination and the like is selectively completed, so that with the support of the auxiliary examination, a clinician can better understand the condition of a patient, and can also make a more scientific and individualized treatment scheme, so that the patient can obtain a better treatment effect (it needs to be explained here that a diabetic patient is only exemplified as one specific disease condition).
During the time when the patient is waiting in line for the doctor, the patient wastes a great deal of waiting time; meanwhile, when a patient needs to perform multiple examinations, the patient often needs to go to different departments to queue for number taking, and some departments are not even in the same building, so that the patient often queues in sequence at random, but because the queuing number of each examination item is different, the patient can happen to meet the condition of more people when queuing for examination, and then the patient needs to spend a lot of time to queue, the examination efficiency of the patient is seriously affected, even serious patients can delay the examination flow of the patient, and the condition of missed examination occurs.
Disclosure of Invention
The invention aims to continuously optimize an intelligent inquiry system by adopting a man-machine interaction mode combining language and behavioral language for patients, improve the accuracy of intelligent inquiry, perform optimized calculation on examination queue and reduce the waiting time of the patients, and provides the intelligent inquiry and queuing examination system for outpatient service.
The technical solution for realizing the purpose of the invention is as follows:
an outpatient intelligent inquiry and queuing inspection system, comprising: the three-dimensional interval coordinates of the positions of the program, the human-computer interaction device, the mobile phone terminal and the three-dimensional human body model are (X + j, Y + m, Z + v), the disease condition parameter B and the medical knowledge map (S, L); the method comprises the following specific steps:
the method comprises the following steps that firstly, a three-dimensional camera array is adopted to collect diagnosis images of doctors, details of specific cases are in one-to-one correspondence, and a case library D is generated; establishing a three-dimensional human body model at a server, and establishing a one-to-one mapping relation between the position of the three-dimensional human body model and a medical knowledge map;
the three-dimensional point coordinates of the position of the three-dimensional human body model are (X, Y, Z), the three-dimensional interval coordinates of the position of the three-dimensional human body model are (X + j, Y + m, Z + v), and j, m and v are changed real numbers;
a medical knowledge map (S, L), S representing medical knowledge and L representing medical logic;
establishing a one-to-one mapping relation between three-dimensional interval coordinates (X + j, Y + m, Z + v) of the position of the three-dimensional human body model and the medical knowledge map (S, L):
（X+j, Y+m, Z+v）→（S，L）；
（S，L）→（X+j, Y+m, Z+v）；
secondly, mapping the language of the patient to the disease position of the three-dimensional human body model by adopting a natural language processing technology NLP, acquiring a three-dimensional image of the patient by adopting a three-dimensional camera array, and mapping the behavior language of the patient to the disease position of the three-dimensional human body model;
the human-computer interaction device consists of a server, a sound input device, a sound output device, a three-dimensional camera array and a three-dimensional stereoscopic display;
the human-computer interaction device adopts a network structure comprising a plurality of sets of sound input equipment, sound output equipment, a three-dimensional camera array and a three-dimensional stereoscopic display, for example, a hospital can adopt a server, a plurality of sets of sound input equipment, sound output equipment, a three-dimensional camera array and a three-dimensional stereoscopic display;
loading an artificial intelligence algorithm by a program in the server;
through sound input equipment, the language of a patient is mapped to the disease position of the three-dimensional human body model by adopting a Natural Language Processing (NLP) technology to generate a disease parameter model of the disease position of the three-dimensional human body model:
（C）→（X+j, Y+m, Z+v,B）；
b is disease parameters, C is natural language processing NLP technology to vectorize the language of the patient, and the disease state of the patient is confirmed through three-dimensional display and sound;
capturing a three-dimensional image and a behavioral language of a patient through a three-dimensional camera array, mapping the disease position of the patient to the disease position of a three-dimensional human body model, and displaying and acoustically confirming the disease state of the patient through a three-dimensional stereoscopic display;
thirdly, combining and calculating an illness state parameter model of an illness state position of the three-dimensional human body model and a medical knowledge map by adopting medical logic to form an original diagnosis, comparing a disease case library D, correcting the original diagnosis to form a primary diagnosis report, recommending examination items, and judging and confirming the primary diagnosis report and the recommended examination items by a doctor;
fourthly, the inspection item adopts a queuing optimization algorithm to form inspection navigation;
and step five, the examination navigation is sent to the mobile phone APP of the patient, the examination is finished by queuing in sequence, and the medical logic is optimized by combining the examination conclusion.
Compared with the prior art, the invention has the remarkable advantages that: 1. establishing a three-dimensional human body model at a server, and establishing a one-to-one mapping relation between the position of the three-dimensional human body model and a medical knowledge map; 2. adopting a Natural Language Processing (NLP) technology to map the language of a patient into the disease position of a three-dimensional human body model, adopting a three-dimensional camera array to collect a three-dimensional image of the patient, and mapping the behavior language of the patient into the disease position of the three-dimensional human body model; mapping the language of the patient into the disease condition position of the three-dimensional human body model and the disease condition parameter B of the disease condition position of the three-dimensional human body model, and virtualizing the disease condition of the patient into the three-dimensional human body model; 3. combining and calculating an illness state parameter model of an illness state position of the three-dimensional human body model and a medical knowledge map by adopting medical logic to form original diagnosis, comparing a disease case library D, correcting the original diagnosis to form a preliminary diagnosis report, recommending an examination item, judging and confirming the preliminary diagnosis report and the recommended examination item by a doctor, and optimizing the medical logic by combining an examination conclusion; 4. and (4) adopting a queuing optimization algorithm for the inspection items to form inspection navigation.
The present invention is described in further detail below with reference to the attached drawing figures.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a flow diagram of an outpatient intelligent interrogation and queuing inspection system;
FIG. 2 is a flow chart of the human-machine interaction of an outpatient intelligent inquiry and queuing inspection system.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
Example 1:
with reference to fig. 1, a flow chart of an outpatient intelligent inquiry and queuing inspection system is shown.
Natural Language Processing (NLP) is a discipline that studies the linguistic problems of human interaction with computers. According to different technical implementation difficulties, such systems can be divided into three types, namely simple matching type, fuzzy matching type and paragraph understanding type.
N (Neuro) refers to the nervous system, including the brain and thought processes. L (linguistics) refers to the language, and more precisely, the process from input of a sensory signal to constituent meaning. P (Programming) refers to a specific set of instructions to be executed for some consequence. It means that the habit of thinking and behavior is the same as the program in computer, and can be changed by updating the software.
The whole process of the patient entering the hospital is as follows:
firstly, man-machine interaction intelligent inquiry
A patient enters a three-dimensional camera array of a human-computer interaction device, the three-dimensional camera array collects image data and transmits the image data to a server, the server compares historical information with registration information, the language of the human-computer interaction device adopts a Natural Language Processing (NLP) technology, and a language conversation mode is established between the human-computer interaction device and the patient; the three-dimensional camera array collects the three-dimensional image of the patient, and the three-dimensional image of the patient is mapped to the standard three-dimensional human body model built by the server because the three-dimensional human body model built by the server is standard, and the standard three-dimensional human body model built by the server is finely adjusted to form the three-dimensional human body model according with the three-dimensional image of the patient; establishing a one-to-one mapping relation between three-dimensional interval coordinates (X + j, Y + m, Z + v) of the position of the three-dimensional human body model and the medical knowledge map (S, L):
（X+j, Y+m, Z+v）→（S，L）；
（S，L）→（X+j, Y+m, Z+v）；
adopting a Natural Language Processing (NLP) technology to map the language of a patient into the disease position of a three-dimensional human body model, adopting a three-dimensional camera array to collect a three-dimensional image of the patient, and mapping the behavior language of the patient into the disease position of the three-dimensional human body model; through sound input equipment, the language of a patient is mapped to the disease position of a three-dimensional human body model by adopting a Natural Language Processing (NLP) technology to generate a disease parameter model of the disease position of the three-dimensional human body model:
（C）→（X+j, Y+m, Z+v,B）。
second, preliminary diagnosis
According to the disease position (X + j, Y + m, Z + v) of the three-dimensional human body model of the patient and the disease state (X + j, Y + m, Z + v, B) of the disease position of the three-dimensional human body model, the program on the server adopts medical logic to combine the disease parameter model of the disease position of the three-dimensional human body model with the medical knowledge map for calculation to form an original diagnosis, compares a disease case library D and corrects the original diagnosis to form a preliminary diagnosis report.
Third, checking item recommendations
And according to the preliminary diagnosis report, adopting medical logic to give a recommendation of the examination item.
Fourth, the doctor confirms
The doctor judges and confirms the preliminary diagnosis report and the recommended examination items according to the disease conditions (X + j, Y + m, Z + v) of the three-dimensional human body model of the patient and the disease conditions (X + j, Y + m, Z + v, B) of the three-dimensional human body model.
Fifthly, checking the queue optimization algorithm
According to the recommended examination items confirmed by doctors, the queuing condition of the examination items is calculated:
checking whether a precondition exists according to the checking item, such as: fasting blood glucose, fasting is required;
the running state N (t) of a single examination item, the total patient number N (t) of the single examination item at the moment t, wherein the patient number N (t) comprises queued patients and the patients being served;
system state probability of individual examination items:
probability of transient state P n (t) represents the probability of the system state N (t) = N at time t,
probability of steady state P n
Figure 988827DEST_PATH_IMAGE001
After the single inspection item queuing system runs for a certain period of time, the probability distribution of the system state of the single inspection item no longer changes with the time t, namely the probability distribution { P { of the system state of the single inspection item at the initial time (t = 0) } n (0) The effect of n > 0} will disappear;
1. captain and queueing captain
(1) queue leader, number of patients in the system of single examination item (n) expected value is recorded as Ls;
the queue length is that the number of the patients waiting for service in the system of a single inspection project is counted as Lq;
2. linger time and wait time
(1) dwell time, which refers to the total dwell time of a patient in a system of individual examination items; the expected value is recorded as Ws;
(2) waiting time, which refers to the queuing waiting time of a patient in the system of single examination items; the expected value, denoted as Wq, E is the service time,
Ws = Wq + E
3. service strength: ρ = λ/μ; lambda is the number of patients queued up per hour, mu is the number of patients that can be examined per hour for a single examination item,
the calculation formula of each index is as follows:
P 0 =1-ρ P 0 =ρ n (1-ρ)
L s =λ/(μ-λ)=ρ/(1-ρ) L q =λ 2 /μ(μ-λ)=ρ 2 /(1-ρ)= L s ρ
W s =1/(μ-λ) W q =λ/(μ-λ)= W s ρ
ρ= λ/μ P(N＞K)=ρ K+1
if the patient needs a plurality of examination items, the waiting time is added in a permutation and combination mode; the parameters of each inspection queue are dynamically calculated, the waiting time of each inspection item is predicted, and the sequence of the inspection queues is optimally arranged.
Sixth, checking navigation
And sending the examination navigation to the mobile phone APP of the patient according to the optimization algorithm of the examination queue.
The seventh step of inspection
The patient is queued for examination.
Example 2:
with reference to fig. 2, a flow chart of human-machine interaction of an outpatient intelligent inquiry and queuing inspection system;
the man-machine interaction device outputs a language to the patient through sound output equipment; a three-dimensional display of the human-computer interaction device outputs a three-dimensional human body model to the patient. The patient inputs the language to the man-machine interaction device through the voice input equipment; the patient inputs the behavioral language to the human-computer interaction device through the three-dimensional camera array.
The patient speaks the illness state to the man-machine interaction device through sound, the language of the patient is mapped to the illness state position of the three-dimensional human body model through the natural language processing NLP technology through the input equipment of the sound, and the illness state parameter model of the illness state position of the three-dimensional human body model is generated, wherein the mapping relation is as follows: (C) → (X + j, Y + m, Z + v, B); the man-machine interaction device outputs a language to the patient through sound output equipment to confirm the illness state of the patient; the three-dimensional display of the man-machine interaction device outputs a three-dimensional human body model to the patient and confirms the position of the illness state of the patient.
The patient indicates the position of the illness state to the human-computer interaction device through the behavioral language, the position of the illness state of the patient is collected through the three-dimensional camera array, the position of the illness state of the patient is mapped to the position of the illness state of the three-dimensional human body model, the human-computer interaction device outputs the language to the patient through the sound output equipment, and the position of the illness state of the patient is confirmed; the three-dimensional display of the man-machine interaction device outputs a three-dimensional human body model to the patient and confirms the position of the illness state of the patient.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (8)

1. An outpatient intelligent inquiry and queuing inspection system, comprising: the three-dimensional interval coordinates of the positions of the program, the human-computer interaction device, the mobile phone terminal and the three-dimensional human body model are (X + j, Y + m, Z + v), the disease condition parameter B and the medical knowledge map (S, L); the method is characterized in that: the method comprises the following specific steps:
the method comprises the following steps that firstly, a three-dimensional camera array is adopted to collect diagnosis images of doctors, details of specific cases are in one-to-one correspondence, and a case library D is generated; establishing a three-dimensional human body model at a server, and establishing a one-to-one mapping relation between the position of the three-dimensional human body model and a medical knowledge map;
secondly, mapping the language of the patient to the disease position of the three-dimensional human body model by adopting a natural language processing technology (NLP), acquiring a three-dimensional image of the patient by adopting a three-dimensional camera array, and mapping the behavior language of the patient to the disease position of the three-dimensional human body model;
thirdly, combining and calculating an illness state parameter model of an illness state position of the three-dimensional human body model and a medical knowledge map by adopting medical logic to form an original diagnosis, comparing a disease case library D, correcting the original diagnosis to form a primary diagnosis report, recommending examination items, and judging and confirming the primary diagnosis report and the recommended examination items by a doctor;
fourthly, a queuing optimization algorithm is adopted for the inspection items to form inspection navigation;
and step five, sending the examination navigation to a mobile phone APP of the patient, queuing in sequence to complete the examination, and optimizing medical logic by combining examination conclusions.
2. The system of claim 1, wherein the system comprises: establishing a one-to-one mapping relation between three-dimensional interval coordinates (X + j, Y + m, Z + v) of the position of the three-dimensional human body model and the medical knowledge map (S, L):
（X+j, Y+m, Z+v）→（S，L）；
（S，L）→（X+j, Y+m, Z+v）。
3. the system of claim 1, wherein the system comprises: the language of the patient is mapped to the disease position of the three-dimensional human body model to generate a disease parameter model of the disease position of the three-dimensional human body model:
（C）→（X+j, Y+m, Z+v,B）。
4. the in-line system of claim 1, wherein said system comprises: the man-machine interaction device comprises a server, a sound input device, a sound output device, a three-dimensional camera array and a three-dimensional stereoscopic display.
5. The system according to any one of claims 1 to 4, wherein: and the program in the server loads an artificial intelligence algorithm.
6. The system according to any one of claims 1 to 4, wherein: and mapping the three-dimensional image of the patient to a standard three-dimensional human body model established by the server, and finely adjusting the standard three-dimensional human body model established by the server to form the three-dimensional human body model conforming to the three-dimensional image of the patient.
7. The in-line system of claim 1, wherein said system comprises: the parameters of each inspection queue are dynamically calculated, the waiting time of each inspection item is predicted, and the sequence of the inspection queues is optimally arranged.
8. The system of claim 1, wherein the system comprises: the patient indicates the position of the illness state to the human-computer interaction device through the behavioral language, the position of the illness state of the patient is collected through the three-dimensional camera array, the position of the illness state of the patient is mapped to the position of the illness state of the three-dimensional human body model, the human-computer interaction device outputs the language to the patient through the sound output equipment, and the position of the illness state of the patient is confirmed; a three-dimensional display of the human-computer interaction device outputs a three-dimensional human body model to the patient and confirms the illness state position of the patient.
CN202210858528.7A 2022-07-21 2022-07-21 Intelligent inquiry and queuing inspection system for outpatient service Pending CN115206548A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116740476A (en) * 2023-08-15 2023-09-12 四川互慧软件有限公司 Automatic human body labeling method based on patient 360 visualization

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116740476A (en) * 2023-08-15 2023-09-12 四川互慧软件有限公司 Automatic human body labeling method based on patient 360 visualization
CN116740476B (en) * 2023-08-15 2023-11-07 四川互慧软件有限公司 Automatic human body labeling method based on patient 360 visualization

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