CN116965794A - Osteoporosis auxiliary diagnosis device based on artificial intelligence and electromagnetic waves - Google Patents
Osteoporosis auxiliary diagnosis device based on artificial intelligence and electromagnetic waves Download PDFInfo
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Classifications
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
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Abstract
The application discloses an auxiliary osteoporosis diagnosis device based on artificial intelligence and electromagnetic waves, wherein the method comprises the following steps: an information input device, an antenna, an electromagnetic wave shielding device, an information processing apparatus, and a voltage controlled oscillator; the information input device is used for: inputting characteristic information of a patient and transmitting the characteristic information of the patient to an information processing device; the voltage controlled oscillator is used for: generating electromagnetic waves with fixed frequency, and transmitting the electromagnetic waves through an antenna to measure the middle phalanx attenuation of the patient; the electromagnetic wave shielding device is used for: protecting the antenna and the voltage controlled oscillator from electromagnetic interference; the information processing apparatus is configured to: obtaining a middle finger bone attenuation value of the patient, performing auxiliary diagnosis by using a trained deep learning model based on the characteristic information of the patient and the middle finger bone attenuation value, and determining whether the patient needs to perform DXA scanning based on an auxiliary diagnosis result. The screening device developed by the application has greater portability and lower manufacturing cost.
Description
Technical Field
The application relates to the technical field of computer science and medicine, in particular to an auxiliary osteoporosis diagnosis device based on artificial intelligence and electromagnetic waves.
Background
This section is intended to provide a background or context to the embodiments of the application that are recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.
Osteoporosis is an advanced skeletal disease characterized by reduced bone density, reduced bone strength, and easily caused bone fracture due to microstructural deterioration of bone tissue, and is manifested by general discomfort, especially lumbago and backache. Affected individuals are at risk of fracture and consequent deterioration in quality of life, compromising their mobility and autonomy. Therefore, early diagnosis and treatment of the disease is necessary to implement preventive measures to alleviate the occurrence of osteoporotic fracture. The diagnosis of the disease is mainly performed by a dual energy X-ray absorption measurement Device (DXA), which can be applied to femur, lumbar vertebra and forearm.
In addition to DXA, other techniques may also help diagnose osteoporosis in clinical studies, such as quantitative computed tomography (Quantitative Computed Tomography, QCT) and quantitative ultrasound (Quantitative Ultrasound, QUS).
Quantitative computed tomography is an imaging technique for measuring the density of a volumetric bone, and the measuring method comprises the steps of adding a phantom on the basis of conventional CT, then simultaneously scanning a lumbar vertebra and a reference phantom, positioning a region of interest on a trabecular bone of a cancellous bone region of each vertebral body on an image acquired by CT, and finally obtaining the value of the density of the cancellous bone of each vertebral body through computer analysis. The QCT can be used for respectively measuring the cortical bone density and the cancellous bone density, and simultaneously can be used for effectively avoiding the influence of pathological factors such as abdominal aortic atherosclerosis, lumbar retrogressive disease, hyperosteogeny hardening and the like on the bone density measurement. However, QCT has a much higher radiation dose per scan than DXA and is also more costly than DXA.
Quantitative ultrasonic QUS is to evaluate bone mineral density of phalanges and lower leg bones of palm by utilizing attenuation and speed of sound, wherein two probes are respectively and coaxially fixed at two sides of a water tank with adjustable water temperature (see fig. 1), when in measurement, the heel is soaked in the water tank, 3 x 3 grid type 9 point penetration scanning is carried out in a 22mm x 22mm area, the earliest and most popular measurement position is selected, the reason of the position is that 90% of the position is cancellous bone, the metabolic update rate is about 8 times of cortical bone, the position is easy to accept by patients, and the two outer side surfaces are flat and parallel, so that measurement errors caused by position change are reduced. However, the measurement site of quantitative ultrasonic waves has a considerable limitation, and generally only calcaneus, wrist, radius, etc. can be measured, which has a low degree of agreement with the osteoporosis diagnosis standard. Moreover, ultrasonic measurement is affected by bone mineral content, bone material and bone structural characteristics, and the sensitivity and specificity of the measurement result are not as good as those of DXA. In addition, although quantitative ultrasound is non-radiative, there are differences between different devices, and different measurements of the same bone site cannot be analyzed without applying standard diagnostic criteria.
None of the existing osteoporosis diagnostic devices provide a more efficient and rapid early diagnosis of disease.
Disclosure of Invention
The embodiment of the application provides an auxiliary osteoporosis diagnosis device based on artificial intelligence and electromagnetic waves, which is used for solving the technical problem that the existing osteoporosis diagnosis device cannot more effectively and more rapidly give early diagnosis of diseases, and comprises the following components: an information input device, an antenna, an electromagnetic wave shielding device, an information processing apparatus, and a voltage controlled oscillator;
the information input device is used for: inputting characteristic information of a patient and transmitting the characteristic information of the patient to an information processing device;
the voltage controlled oscillator is used for: generating electromagnetic waves with fixed frequency, and transmitting the electromagnetic waves through an antenna to measure the middle phalanx attenuation of the patient;
the electromagnetic wave shielding device is used for: protecting the antenna and the voltage controlled oscillator from electromagnetic interference;
the information processing apparatus is configured to: obtaining a middle finger bone attenuation value of the patient, performing auxiliary diagnosis by using a trained deep learning model based on the characteristic information of the patient and the middle finger bone attenuation value, and determining whether the patient needs to perform DXA scanning based on an auxiliary diagnosis result.
Compared with the technical scheme that Quantitative Computed Tomography (QCT) and quantitative ultrasonic QUS technologies help to diagnose osteoporosis in clinical research in the prior art, the embodiment of the application provides an auxiliary diagnosis device for osteoporosis based on artificial intelligence and electromagnetic waves, which comprises an information input device, an antenna, an electromagnetic wave shielding device, information processing equipment and a voltage-controlled oscillator, wherein the auxiliary diagnosis device is used for diagnosing osteoporosis in clinical research by the information input device: inputting characteristic information of a patient and transmitting the characteristic information of the patient to an information processing device; electromagnetic waves with fixed frequency are generated through the controlled oscillator, and the attenuation of the middle phalanx of the patient is measured through electromagnetic wave transmission through the antenna; the antenna and the voltage-controlled oscillator are protected from electromagnetic interference by the electromagnetic wave shielding device; the application evaluates the density of middle phalanges and screens osteoporosis based on a measurement program of electromagnetic wave propagation in phalanges, and uses a deep learning method to identify and assist in diagnosis of osteoporosis, and an early detection model can be developed, which has greater portability and lower manufacturing cost.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. In the drawings:
FIG. 1 is a schematic illustration of indirect calcaneus ultrasonic penetration measurement;
FIG. 2 is a block diagram of an auxiliary osteoporosis diagnosis device based on artificial intelligence and electromagnetic waves in an embodiment of the application;
FIG. 3 is a schematic illustration of electromagnetic wave transmission measurement of the attenuation of a patient's middle phalanx in an embodiment of the present application;
FIG. 4 is a schematic diagram of an antenna structure according to an embodiment of the present application;
FIG. 5 is a radiation pattern of an antenna according to an embodiment of the present application;
fig. 6 is a schematic diagram of an operation flow of the osteoporosis auxiliary diagnosis based on artificial intelligence and electromagnetic waves in the embodiment of the application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the embodiments of the present application will be described in further detail with reference to the accompanying drawings. The exemplary embodiments of the present application and their descriptions herein are for the purpose of explaining the present application, but are not to be construed as limiting the application.
The technical scheme of the application obtains, stores, uses, processes and the like the data, which all meet the relevant regulations of national laws and regulations.
Fig. 2 is a block diagram of an auxiliary diagnosis device for osteoporosis based on artificial intelligence and electromagnetic waves according to an embodiment of the present application, and as shown in fig. 2, the auxiliary diagnosis device for osteoporosis based on artificial intelligence and electromagnetic waves comprises: an information input device, an antenna, an electromagnetic wave shielding device, an information processing apparatus, and a voltage controlled oscillator;
the information input device is used for: inputting characteristic information of a patient and transmitting the characteristic information of the patient to an information processing device;
the voltage controlled oscillator is used for: generating electromagnetic waves with fixed frequency, and transmitting the electromagnetic waves through an antenna to measure the middle phalanx attenuation of the patient;
the electromagnetic wave shielding device is used for: protecting the antenna and the voltage controlled oscillator from electromagnetic interference;
the information processing apparatus is configured to: obtaining a middle finger bone attenuation value of the patient, performing auxiliary diagnosis by using a trained deep learning model based on the characteristic information of the patient and the middle finger bone attenuation value, and determining whether the patient needs to perform DXA scanning based on an auxiliary diagnosis result.
In particular, the information input device may be a tablet (for filling in patient features). An antenna (for performing electromagnetic wave transmission to measure attenuation of a patient's phalanx), an electromagnetic wave shielding material (for protecting the antenna and the voltage controlled oscillator from electromagnetic interference), an information processing device (for operating analog-to-digital conversion, having the ability to transmit results in a graphical environment through a computer network, perform data analysis, and perform calculation in a neural network by receiving programming instructions), and a voltage controlled oscillator (for facilitating generation of a stable frequency when measuring attenuation of a patient's phalanx, the attenuation being due to bone tissue by electromagnetic signal propagation, and the degree of attenuation being dependent on the porosity of the bone to perform bone density assessment of the patient's phalanx).
In the embodiment of the present application, as shown in fig. 3, the antenna includes a transmitting antenna and a receiving antenna, where the transmitting antenna is connected with a voltage-controlled oscillator;
the voltage-controlled oscillator generates electromagnetic waves with fixed frequency, the electromagnetic waves are sent out through the transmitting antenna, the electromagnetic waves pass through the middle phalanx of the patient, and then the receiving antenna receives the electromagnetic waves subjected to frequency attenuation (the electromagnetic waves pass through the middle phalanx, and the difference between the frequency of the transmitting antenna and the frequency of the receiving antenna is calculated to be the middle phalanx attenuation value).
In the embodiment of the application, the antenna adopts a pair of yagi-uda antennas, wherein one antenna is used as a transmitter, and the other antenna is used as a receiver.
The antenna is characterized in that the antenna is structurally an active oscillator with an upper half part of a metal split resonant ring SRR structure, a lower half part of the antenna is a feed balun for realizing 180-degree phase difference, copper is coated on the back surface of a dielectric plate of the antenna, the dielectric plate is a ground plane and is a reflecting oscillator of a yagi antenna, an active oscillator arm of the yagi antenna is used as one side of the SRR structure, gaps among the active oscillator arms are used as openings of an outer ring of the SRR structure, and the SRR structure is rectangular.
Specifically, an antenna is a device that radiates electromagnetic waves into free space. Typically, the antenna is powered by a transmission line, such as a microstrip line or coaxial cable, to transmit signals from a transmission source to the antenna. In the existing type, the yagi-uda antenna (yagi antenna) has high directivity and thus high gain in the maximum energy radiation direction. In order to obtain the accuracy of patient information, the application uses a pair of yagi-uda antennas, one is a transmitter and the other is a receiver, the working frequency range is 2.45GHz, the stability of information transmission is ensured, and the application is provided by a microstrip line (the microstrip line is a microwave transmission line formed by a single conductor strip supported on a dielectric substrate). A yagi antenna is a steerable antenna, which is composed of a source element and a plurality of passive elements placed on the same plane and perpendicular to a metal rod connecting their centers. Typically one passive element is a reflector and the remaining passive elements are directors.
The upper half 1 of the antenna is an active oscillator in a metal split resonant ring (Split Ring Resonator, SRR) structure, the lower half 2 is a feed balun for realizing 180 DEG phase difference, and the antenna structure is shown in fig. 4. The dielectric plate adopted by the method is a Rogers plate with a dielectric constant of 9.8. The back of the dielectric plate 3 is coated with copper, which is both the ground plane and the reflective element of the quasi-yagi antenna. The active dipole arms 4 of the yagi antenna are used as one side of the SRR structure, and the gaps between the dipole arms are used as openings of the outer ring of the SRR structure. The square structure of the SRR structure is changed to a rectangular structure in consideration of the size of the antenna.
The yagi mode resonance frequency point of the designed antenna is set to 2.45GHz according to microstrip quasi-yagi antenna characteristics to determine the preliminary size of the antenna, and is made of 1.6 mm thick aluminum to ensure high-standard electromagnetic shielding. By simulation, the main dimensions of the antenna are shown in Table 1, and FIG. 5 is a radiation pattern of the antenna, where E-Plane represents a Plane perpendicular to the direction of the electric field and H-Plane represents a Plane perpendicular to the direction of the magnetic field.
TABLE 1 antenna principal dimensions (Unit: mm)
| Antenna parameters | Size of the device |
| L 1 | 20 |
| W 1 | 9.09 |
| L 2 | 13.5 |
| W 2 | 5 |
| S | 2 |
| W 1 | 2 |
| W 1 | 2 |
In the embodiment of the application, the electromagnetic wave shielding device adopts AN Eccosorb AN-79 broadband free space absorber (the frequency range is 600MHz-40 GHz) as AN electromagnetic wave shielding material. The Eccosorb AN-79 wave absorbing material is covered in the sealed box of the sensitive hardware circuit (antenna and voltage-controlled oscillator) to achieve the effect of shielding electromagnetic interference.
In an embodiment of the present application, the information processing apparatus includes radio frequency power detectors (2) and a processor;
the radio frequency power detector is used for: the device is respectively connected with a voltage-controlled oscillator (or a transmitting antenna is connected) and a receiving antenna, the frequencies of electromagnetic waves acquired from the voltage-controlled oscillator and the receiving antenna are converted into voltages (2), and the voltages are sent to a processor for processing; i.e. one measuring the frequency of the electromagnetic wave of the voltage controlled oscillator (i.e. of the transmitting antenna) and one measuring the frequency of the electromagnetic wave of the receiving antenna, both convert the frequency of the received electromagnetic wave into a voltage, which is sent to the processor for processing.
The processor is configured to: and obtaining a middle phalange attenuation value of the patient according to the voltage, performing auxiliary diagnosis by using a trained deep learning model based on the characteristic information and the middle phalange attenuation value of the patient, and determining whether the patient needs to perform DXA scanning based on an auxiliary diagnosis result.
In particular, the Voltage Controlled Oscillator (VCO) of the present application may generate a sinusoidal signal whose frequency depends on the voltage applied to its input. A radio frequency power detector is connected with the voltage controlled oscillator, or connected with the transmitting antenna, and the frequency of the transmitted electromagnetic wave can be obtained by both connection modes. The other radio frequency power detector is connected with the receiving antenna to obtain the frequency of the electromagnetic wave at the receiving antenna. The radio frequency power detector converts the frequencies of electromagnetic waves acquired from the voltage controlled oscillator and the receiving antenna into voltages, respectively, and then supplies the two voltages to the processor for processing thereof. The processor calculates the difference between the two voltages and takes this difference as the patient's median phalangeal attenuation value.
The voltage-controlled oscillator has good frequency stability, high control sensitivity and wide frequency modulation range, and is convenient for generating stable frequency when measuring phalangeal attenuation in a patient.
In an embodiment of the present application, the characteristic information of the patient includes risk factors associated with osteoporosis;
the processor is further configured to: and (3) taking the risk factors related to osteoporosis and the middle finger bone attenuation value as characteristics, and inputting the characteristics into a support vector machine for training to obtain a trained deep learning model.
In particular, the risk factors associated with osteoporosis used in the present application include: 1. race 2, education 3, occupation 4, marital 5, monthly income 6, gender 7, age 8, weight 9, height 10, weight index 11, waist-to-hip ratio 12, sum of four skin fold thicknesses 13, postmenopausal status 14, breast feeding time. The risk factors and the middle phalangeal attenuation values are taken as characteristics to be combined and input into a support vector machine, 112 cases of data sets are collected clinically, marked by 5 professional doctors, and then the data sets are input into the support vector machine for training. The training is completed by generating a model that is used to indicate whether the patient needs to be scanned for DXA (dual energy X-ray absorptiometry).
In an embodiment of the present application, the method further includes: and the dual-energy X-ray absorption measurement equipment is used for carrying out DXA scanning when the patient is determined to need to carry out DXA scanning based on the auxiliary diagnosis result, obtaining bone density scanning values, and carrying out osteoporosis screening through the bone density scanning values.
In an embodiment of the present application, the method further includes: cloud database and diagnosis system;
the cloud database is used for: receiving a bone mineral density scanning value sent by dual-energy X-ray absorption measurement equipment;
the diagnostic system is for: osteoporosis screening is performed by the bone mineral density scan value.
Fig. 6 is a schematic diagram of an operation flow of the osteoporosis auxiliary diagnosis based on artificial intelligence and electromagnetic waves in the embodiment of the application. First, the operator fills out the patient's features on the flat panel electronic form. Then, electromagnetic waves with fixed frequency are generated through the voltage-controlled oscillator, electromagnetic wave transmission is carried out through the antenna to measure the attenuation of the middle phalanx of the patient (the electromagnetic waves pass through the middle phalanx, and the difference between the frequency of the transmitting antenna and the frequency of the receiving antenna is calculated to be the attenuation value of the middle phalanx). Finally, a processor (i.e. an information analysis system (network side)) indicates whether the patient needs to perform DXA (dual energy X-ray absorptiometry) scanning according to the characteristics and signal attenuation information of the patient combined by using the trained deep learning model. If DXA scanning is required, the device displays the obtained bone mineral density scanning value, the data is sent to a cloud database for storage, and a doctor can use a diagnosis system to screen osteoporosis based on the bone mineral density scanning value.
The application evaluates the density of the phalanges and screens osteoporosis by a hybrid device consisting of antennas and developing measurement procedures based on the propagation of electromagnetic waves in the phalanges. Has the following beneficial effects:
(1) The application screens the high risk group of osteoporosis or fracture by combining artificial intelligence and risk factors, and predicts that the risk group of osteoporosis may lighten the huge economic burden of the osteoporosis fracture on the medical system.
(2) The screening device developed by the application has greater portability and lower manufacturing cost.
(3) And the network is utilized to carry out data transmission of patients, and the database is utilized to store, so that different characteristic information can be conveniently collected to regulate and optimize the artificial intelligent network. A large amount of patient data is stored, the neural network is convenient to train, the data can contain data of different sexes and species, the neural network can be used for counteracting the sex later, and the species can be used for screening the difference of osteoporosis.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the application, and is not meant to limit the scope of the application, but to limit the application to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the application are intended to be included within the scope of the application.
Claims (10)
1. An artificial intelligence and electromagnetic wave based osteoporosis auxiliary diagnosis device, comprising: an information input device, an antenna, an electromagnetic wave shielding device, an information processing apparatus, and a voltage controlled oscillator;
the information input device is used for: inputting characteristic information of a patient and transmitting the characteristic information of the patient to an information processing device;
the voltage controlled oscillator is used for: generating electromagnetic waves with fixed frequency, and transmitting the electromagnetic waves through an antenna to measure the middle phalanx attenuation of the patient;
the electromagnetic wave shielding device is used for: protecting the antenna and the voltage controlled oscillator from electromagnetic interference;
the information processing apparatus is configured to: obtaining a middle finger bone attenuation value of the patient, performing auxiliary diagnosis by using a trained deep learning model based on the characteristic information of the patient and the middle finger bone attenuation value, and determining whether the patient needs to perform DXA scanning based on an auxiliary diagnosis result.
2. The artificial intelligence and electromagnetic wave based osteoporosis auxiliary diagnostic device of claim 1, wherein the antenna comprises a transmitting antenna and a receiving antenna, wherein the transmitting antenna is connected to a voltage controlled oscillator;
the voltage-controlled oscillator generates electromagnetic waves with fixed frequency, the electromagnetic waves are sent out through the transmitting antenna, and the electromagnetic waves are received by the receiving antenna after passing through the middle phalanx of the patient.
3. The artificial intelligence and electromagnetic wave based osteoporosis auxiliary diagnostic device of claim 1, wherein the antenna employs a pair of yagi-uda antennas, one of which serves as a transmitter and the other as a receiver.
4. The auxiliary diagnosis device for osteoporosis based on artificial intelligence and electromagnetic waves according to claim 3, wherein the antenna is structured as an active oscillator with an upper half part of a metal split resonant ring SRR structure, a lower half part of the antenna is a feed balun for realizing 180 ° phase difference, the back of a dielectric plate of the antenna is coated with copper, the dielectric plate is a ground plane and is a reflective oscillator of a yagi antenna, an active oscillator arm of the yagi antenna is used as one side of the SRR structure, gaps among the active oscillator arms are used as openings of an outer ring of the SRR structure, and the SRR structure is rectangular.
5. The artificial intelligence and electromagnetic wave based osteoporosis auxiliary diagnostic device of claim 1, wherein the antenna operating frequency range is 2.45GHz.
6. The artificial intelligence and electromagnetic wave based osteoporosis auxiliary diagnostic device of claim 1, wherein the electromagnetic wave shielding device employs AN Eccosorb AN-79 broadband free space absorber.
7. The artificial intelligence and electromagnetic wave based osteoporosis auxiliary diagnostic apparatus of claim 1, wherein the information processing device comprises a radio frequency power detector and a processor;
the radio frequency power detector is used for: the device is connected with the voltage-controlled oscillator and the receiving antenna, converts the frequency of electromagnetic waves acquired from the voltage-controlled oscillator and the receiving antenna into voltage, and sends the voltage to the processor for processing;
the processor is configured to: and obtaining a middle phalange attenuation value of the patient according to the voltage, performing auxiliary diagnosis by using a trained deep learning model based on the characteristic information and the middle phalange attenuation value of the patient, and determining whether the patient needs to perform DXA scanning based on an auxiliary diagnosis result.
8. The artificial intelligence and electromagnetic wave based osteoporosis auxiliary diagnostic device of claim 7, wherein the patient characteristic information includes risk factors associated with osteoporosis;
the processor is further configured to: and (3) taking the risk factors related to osteoporosis and the middle finger bone attenuation value as characteristics, and inputting the characteristics into a support vector machine for training to obtain a trained deep learning model.
9. The artificial intelligence and electromagnetic wave based osteoporosis auxiliary diagnostic device according to claim 1, further comprising: and the dual-energy X-ray absorption measurement equipment is used for carrying out DXA scanning when the patient is determined to need to carry out DXA scanning based on the auxiliary diagnosis result, obtaining bone density scanning values, and carrying out osteoporosis screening through the bone density scanning values.
10. The artificial intelligence and electromagnetic wave based osteoporosis auxiliary diagnostic device according to claim 1, further comprising: cloud database and diagnosis system;
the cloud database is used for: receiving a bone mineral density scanning value sent by dual-energy X-ray absorption measurement equipment;
the diagnostic system is for: osteoporosis screening is performed by the bone mineral density scan value.
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| CN202210420291.4A CN116965794A (en) | 2022-04-21 | 2022-04-21 | Osteoporosis auxiliary diagnosis device based on artificial intelligence and electromagnetic waves |
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| CN202210420291.4A CN116965794A (en) | 2022-04-21 | 2022-04-21 | Osteoporosis auxiliary diagnosis device based on artificial intelligence and electromagnetic waves |
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| CN202210420291.4A Pending CN116965794A (en) | 2022-04-21 | 2022-04-21 | Osteoporosis auxiliary diagnosis device based on artificial intelligence and electromagnetic waves |
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