CN111951934A - Novel acromegaly screening system and screening method thereof - Google Patents
Novel acromegaly screening system and screening method thereof Download PDFInfo
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Abstract
The invention discloses a novel acromegaly screening system and a screening method thereof, and the system comprises a pituitary tumor intelligent health management platform, a hand characteristic database and an artificial intelligent early screening system; the pituitary adenoma intelligent health management platform is used for collecting hand photos of a person to be tested; the intelligent pituitary adenoma health management platform stores the collected hand photos in a hand characteristic database; the artificial intelligence early screening system comprises a convolutional neural network; the convolutional neural network carries out artificial intelligent deep learning on the hand pictures in the hand feature database, so that a deep learning model is established and operated, and repeated verification, correction and data classification are carried out; the artificial intelligence early screening system outputs screening data after carrying out artificial intelligence background measurement and calculation on the hand photos, and preliminarily determines whether the patient is the acromegaly patient according to the screening data; the invention has low cost and high efficiency, replaces the examination of hematology/nuclear magnetic resonance and the like, and effectively reduces the investment of manpower and material resources for screening.
Description
Technical Field
The invention relates to the technical field of medical instruments, in particular to a novel acromegaly screening system and a screening method thereof.
Background
Pituitary adenomas are common intracranial tumors, accounting for about 15% of intracranial tumors, and the onset of the disease is on the rise in recent years. Pituitary Growth Hormone (GH) adenomas are common functional pituitary adenomas, manifesting as acromegaly in adults. Although the pituitary-derived acromegaly is a benign lesion, the symptoms of visual dysfunction, hypophysis hypofunction, headache and the like are caused by the fact that tumors are enlarged and press structures such as visual cross, normal pituitary, cavernous sinus and the like; meanwhile, the excessive GH secretion of the tumor leads to the increase of the level of Insulin-like growth factor 1 (IGF-1), which can cause the diseases of soft tissue overgrowth, hypertrophy of internal organs such as heart, lung, liver and kidney, osteoarthritis, sleep apnea, diabetes, hypertension, arrhythmia, congestive heart failure and the like, and seriously affect the quality of life of the patient. Studies have shown that acromegaly patients have a mortality rate of more than 2 times that of the normal population, with an average life of about 50 years.
Due to the lack of medical and patient education in China, early detection rate and diagnosis rate of acromegaly patients are low, and the patients are discovered to grow aggressively when tumors grow. Most patients have slow disease development, hidden clinical symptoms and no specific expression, thereby delaying accurate diagnosis. About 35% of pituitary adenomas grow invasively, 0.1-0.2% of pituitary adenomas develop into malignant tumors, if the pituitary adenomas cannot be found early, the treatment difficulty is obviously increased when the symptoms are obvious, the prognosis is poor, the family economy is seriously affected, and the national medical insurance and social burden are increased.
At present, pituitary adenoma screening is mainly based on nuclear magnetic resonance enhanced scanning and pituitary hormone level detection, and doctors with abundant clinical experience make preliminary diagnosis and establish a treatment scheme. However, the following problems still exist in the current early screening of acromegaly patients: 1) the imaging nuclear magnetic resonance scanning cost of the acromegaly patient is high, the social and family burden of the patient is increased, the hematology examination is invasive puncture examination, and the examination efficiency is low. 2) The diagnosis result is easily influenced by the subjective factors of doctors; because the current medical level is not uniform, the energy of excellent doctors is limited, and the misdiagnosis and missed diagnosis ratio is too high. 3) Pituitary adenomas require a lifelong follow-up, and it is difficult for patients to perform periodic magnetic resonance scans to determine disease progression.
Disclosure of Invention
The invention aims to provide a novel acromegaly screening system and a screening method thereof, which have high screening efficiency, solve the problem of uneven distribution of dominant medical resources and reduce low misdiagnosis and missed diagnosis.
The invention is realized by the following technical scheme:
a novel acromegaly screening system comprises an intelligent health management platform for pituitary adenoma, a hand characteristic database and an artificial intelligent early screening system; the pituitary adenoma intelligent health management platform is used for collecting hand photos of a person to be detected; the intelligent pituitary adenoma health management platform stores the collected hand pictures in the hand characteristic database; the artificial intelligence early screening system comprises a convolutional neural network; the convolutional neural network carries out artificial intelligent deep learning on the hand pictures in the hand feature database, so that a deep learning model is established and operated, and repeated verification, correction and data classification are carried out; the artificial intelligence early screening system outputs screening data after carrying out artificial intelligence background measurement and calculation on the hand photos, and preliminarily determines whether the patient is the acromegaly patient according to the screening data.
Further, if the value of the screening data is more than 0.8, the patient is preliminarily determined to be acromegaly; and if the numerical value of the screening data is less than 0.8, the patient is the patient with non-acromegaly.
Further, the intelligent pituitary adenoma health management platform comprises a hospital examination acquisition platform and an artificial intelligent pituitary adenoma screening online platform.
Further, the hand characteristic database comprises a hand characteristic database of acromegaly patients and a hand characteristic database of normal population.
Further, a novel acromegaly screening method comprises the following steps:
step (1), a person to be measured takes a picture of a hand;
step (2), a person to be tested logs in an intelligent pituitary adenoma health management platform, enters an early screening page, uploads a hand picture to a website and stores the hand picture in a hand characteristic database;
step (3), the artificial intelligence early screening system carries out artificial intelligence background measurement and calculation on the hand photos and outputs screening data;
step (4), if the screening data is less than 0.8, the person to be tested is a patient with non-acromegaly; if the value of the screening data is more than 0.8, the patient with acromegaly is preliminarily confirmed, and further hematology or nuclear magnetic resonance examination is recommended.
Further, in the step (3), when the artificial intelligent background measurement and calculation are performed on the hand picture, the data of the hand picture is calculated based on the visual deep learning of the convolutional neural network, the calculated data is verified, and the error data existing in the visual deep learning process is repeatedly corrected.
Further, in the step (3), before performing the artificial intelligence background measurement and calculation on the hand picture, the artificial intelligence early screening system performs data cleaning on the hand picture first, performs rechecking and verification on the hand picture data, deletes duplicate information, corrects the existing errors, and provides data consistency.
Further, in the step (3), the screening data can be used for a physical examination screening system, clinical efficacy observation, knowledge base and early warning.
The invention has the beneficial effects that:
the intelligent health management platform for the pituitary adenoma, the hand characteristic database and the artificial intelligent early screening system are arranged; the pituitary adenoma intelligent health management platform is used for collecting hand photos of a person to be tested; the intelligent pituitary adenoma health management platform stores the collected hand photos in a hand characteristic database; the artificial intelligence early screening system comprises a convolutional neural network; the convolutional neural network carries out artificial intelligent deep learning on the hand pictures in the hand feature database, so that a deep learning model is established and operated, and repeated verification, correction and data classification are carried out; the artificial intelligence early screening system outputs screening data after carrying out artificial intelligence background measurement and calculation on the hand picture, and preliminarily determines whether the patient is the acromegaly patient according to the screening data. The invention has low cost, is freely opened to the society, replaces the examination of hematology/nuclear magnetic resonance and the like, effectively reduces the investment of manpower and material resources for screening, has high efficiency, is far higher than the diagnosis level of human doctors, finds the patient at an early stage, is beneficial to reducing the culture period of pituitary adenoma professional medical talents, improves the overall medical service capability, shortens the diagnosis and treatment time and cost of the patient, improves the coverage rate of high-quality medical resources, reduces the imbalance of regional medical resources and reduces the misdiagnosis and missed diagnosis.
Drawings
FIG. 1 is a schematic diagram of the deep learning model building of the convolutional neural network according to the embodiment of the present invention;
FIG. 2 is a schematic view showing the visualization of the hand characteristics of a patient with pituitary adenoma of Grad-CAM growth hormone type according to an embodiment of the present invention;
FIG. 3 is a table showing the comparison between the identification of a patient with acromegaly by a neurosurgeon and the screening system of an embodiment of the present invention;
FIG. 4 is a schematic diagram of an upper platform of an artificial intelligence screening line for pituitary adenomas according to an embodiment of the present invention;
FIG. 5 is a schematic flow chart of a normal person using a acromegaly screening system in accordance with an embodiment of the present invention;
FIG. 6 is a schematic flow chart of a suspected patient with acromegaly using a screening system for acromegaly according to an embodiment of the present invention;
fig. 7 is a schematic structural framework diagram of the novel acromegaly screening system according to the embodiment of the invention.
Detailed Description
The invention will be described in detail with reference to the drawings and specific embodiments, which are illustrative of the invention and are not to be construed as limiting the invention.
It should be noted that all the directional indications (such as up, down, left, right, front, back, upper end, lower end, top, bottom … …) in the embodiments of the present invention are only used to explain the relative position relationship between the components, the movement situation, etc. in a specific posture (as shown in the drawings), and if the specific posture is changed, the directional indication is changed accordingly.
In the present invention, unless expressly stated or limited otherwise, the term "coupled" is to be interpreted broadly, e.g., "coupled" may be fixedly coupled, detachably coupled, or integrally formed; can be mechanically or electrically connected; they may be directly connected or indirectly connected through intervening media, or they may be connected internally or in any other suitable relationship, unless expressly stated otherwise. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In addition, the descriptions related to "first", "second", etc. in the present invention are only for descriptive purposes and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature; in addition, technical solutions between various embodiments may be combined with each other, but must be realized by a person skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present invention.
A novel acromegaly screening system comprises an intelligent health management platform for pituitary adenoma, a hand characteristic database and an artificial intelligent early screening system; the pituitary adenoma intelligent health management platform is used for collecting hand photos of a person to be detected; the intelligent pituitary adenoma health management platform stores the collected hand pictures in the hand characteristic database; the artificial intelligence early screening system comprises a convolutional neural network; the convolutional neural network carries out artificial intelligent deep learning on the hand pictures in the hand feature database, so that a deep learning model is established and operated, and repeated verification, correction and data classification are carried out; the artificial intelligence early screening system outputs screening data after carrying out artificial intelligence background measurement and calculation on the hand photos, and preliminarily determines whether the patient is the acromegaly patient according to the screening data. The invention has low cost, is freely opened to the society, replaces the examination of hematology/nuclear magnetic resonance and the like, effectively reduces the investment of manpower and material resources for screening, has high efficiency, is far higher than the diagnosis level of human doctors, finds the patient at an early stage, is beneficial to reducing the culture period of pituitary adenoma professional medical talents, improves the overall medical service capability, shortens the diagnosis and treatment time and cost of the patient, improves the coverage rate of high-quality medical resources, reduces the imbalance of regional medical resources and reduces the misdiagnosis and missed diagnosis.
Referring to fig. 1 and 2, internal verification of the GH pituitary adenoma artificial intelligence early screening system includes collecting 992 hand photographs of patients with growth hormone pituitary adenoma, performing artificial intelligence deep learning by using a convolutional neural network, and obtaining a system for identifying pituitary adenoma through the hand photographs (sensitivity 0.983, specificity 0.920, PPV 0.966, NPV 0.958, and F1-score 0.974), so that hand feature visualization of acromegaly is realized, a convenient and efficient tool is provided for screening patients with growth hormone pituitary adenoma, and labor and social costs are saved.
External verification of GH pituitary adenoma artificial intelligence early screening system
Meanwhile, in order to further evaluate the effectiveness of the artificial intelligent pituitary adenoma screening system, the backs and image data of 100 scoliosis patients with different degrees of severity and 100 normal persons are selected for external verification of the system, and the result shows that the artificial intelligent pituitary adenoma screening accuracy is superior to that of the screening result of 6 expert groups. In the external verification process, the human expert uses about 30 minutes to perform the identification and diagnosis of 200 cases of data (average 10s per photo reading), and the time required for artificial intelligence is only about 3 minutes (average 1.0s per photo reading), which is obviously less than that of the human expert (fig. 3). The result indicates that the artificial intelligent GH pituitary adenoma screening system is adopted to replace manual screening, so that the investment of manpower and material resources for screening large-scale GH pituitary adenoma patients can be reduced, the culture period of professional medical talents for pituitary adenoma can be reduced, the overall medical service capability can be improved, the diagnosis and treatment time and cost of patients can be shortened, the coverage rate of high-quality medical resources can be improved, and the imbalance of regional medical resources can be reduced.
Specifically, in this embodiment, if the value of the screening data is greater than 0.8, it is primarily determined that the patient is acromegaly; and if the numerical value of the screening data is less than 0.8, the patient is the patient with non-acromegaly.
Specifically, in the embodiment, the intelligent health management platform for pituitary adenoma includes a hospital examination acquisition platform and an artificial intelligent screening line platform for pituitary adenoma. It should be noted that, referring to FIG. 4, based on the development result of GH type pituitary adenoma early screening system, platform https:// www.aipituitary.com on artificial intelligence screening line for pituitary adenoma has been opened. And a large-scale screening scene platform is realized.
Specifically, in this embodiment, the hand feature database includes a hand feature database of acromegaly patients and a hand feature database of normal people.
Referring to fig. 7, in particular, in this embodiment, a novel acromegaly screening method includes the following steps:
step (1), a person to be measured takes a picture of a hand;
step (2), a person to be tested logs in an intelligent pituitary adenoma health management platform, enters an early screening page, uploads a hand picture to a website and stores the hand picture in a hand characteristic database;
step (3), the artificial intelligence early screening system carries out artificial intelligence background measurement and calculation on the hand photos and outputs screening data;
step (4), if the screening data is less than 0.8, the person to be tested is a patient with non-acromegaly; if the value of the screening data is more than 0.8, the patient with acromegaly is preliminarily confirmed, and further hematology or nuclear magnetic resonance examination is recommended.
Referring to fig. 5, specifically, a normal person takes a hand photo of the normal person, then logs on an intelligent health management platform for pituitary adenoma in south China, enters an early screening page, uploads the hand photo to a website, and an artificial intelligent early screening system performs artificial intelligent background calculation on the hand photo and outputs screening data, wherein the screening data is displayed to be less than 0.8, and the possibility of suffering from acromegaly is eliminated.
Referring to fig. 6, specifically, a suspected acromegaly patient takes a hand picture of the suspected acromegaly patient, then logs on an intelligent health management platform for pituitary adenoma in south China, enters an early screening page, uploads the hand picture to a website, and an artificial intelligent early screening system performs artificial intelligent background measurement and calculation on the hand picture and outputs screening data, wherein the screening data is displayed to be greater than 0.8, and the suspected acromegaly patient is preliminarily confirmed to be recommended to further perform hematology or nuclear magnetic resonance examination.
Specifically, in the embodiment, in the step (3), when the artificial intelligent background measurement and calculation are performed on the hand picture, the hand picture data is calculated based on the visual depth learning of the convolutional neural network, the calculated data is verified, and the error data existing in the visual depth learning process is repeatedly corrected.
Specifically, in the scheme of this embodiment, in the step (3), before performing the artificial intelligence background measurement and calculation on the hand picture, the artificial intelligence early screening system performs data cleaning on the hand picture first, performs review and verification on the hand picture data, deletes duplicate information, corrects an existing error, and provides data consistency.
Specifically, in the embodiment, in the step (3), the screening data may be used in a physical examination screening system, clinical efficacy observation, knowledge base, and early warning.
The technical solutions provided by the embodiments of the present invention are described in detail above, and the principles and embodiments of the present invention are explained herein by using specific examples, and the descriptions of the embodiments are only used to help understanding the principles of the embodiments of the present invention; meanwhile, for a person skilled in the art, according to the embodiments of the present invention, there may be variations in the specific implementation manners and application ranges, and in summary, the content of the present description should not be construed as a limitation to the present invention.
Claims (8)
1. A novel acromegaly screening system is characterized in that: the intelligent pituitary adenoma early screening system comprises a pituitary adenoma intelligent health management platform, a hand characteristic database and an artificial intelligent early screening system; the pituitary adenoma intelligent health management platform is used for collecting hand photos of a person to be detected; the intelligent pituitary adenoma health management platform stores the collected hand pictures in the hand characteristic database; the artificial intelligence early screening system comprises a convolutional neural network; the convolutional neural network carries out artificial intelligent deep learning on the hand pictures in the hand feature database, so that a deep learning model is established and operated, and repeated verification, correction and data classification are carried out; the artificial intelligence early screening system outputs screening data after carrying out artificial intelligence background measurement and calculation on the hand photos, and preliminarily determines whether the patient is the acromegaly patient according to the screening data.
2. The novel acromegaly screening system of claim 1, wherein: if the numerical value of the screening data is more than 0.8, the patient is preliminarily determined to be the acromegaly patient; and if the numerical value of the screening data is less than 0.8, the patient is the patient with non-acromegaly.
3. The novel acromegaly screening system of claim 2, wherein: the intelligent pituitary adenoma health management platform comprises a hospital physical examination acquisition platform and an artificial intelligent pituitary adenoma screening online platform.
4. The novel acromegaly screening system of claim 3, wherein: the hand characteristic database comprises a hand characteristic database of acromegaly patients and a hand characteristic database of normal crowds.
5. The novel acromegaly screening method as claimed in claim 4, which comprises the following steps:
step (1), a person to be measured takes a picture of a hand;
step (2), a person to be tested logs in an intelligent pituitary adenoma health management platform, enters an early screening page, uploads a hand picture to a website and stores the hand picture in a hand characteristic database;
step (3), the artificial intelligence early screening system carries out artificial intelligence background measurement and calculation on the hand photos and outputs screening data;
step (4), if the screening data is less than 0.8, the person to be tested is a patient with non-acromegaly; if the value of the screening data is more than 0.8, the patient with acromegaly is preliminarily confirmed, and further hematology or nuclear magnetic resonance examination is recommended.
6. The novel acromegaly screening method of claim 5, wherein: in the step (3), when the artificial intelligent background measurement and calculation are carried out on the hand photos, the hand photo data are calculated based on the visual deep learning of the convolutional neural network, the calculated data are verified, and the error data existing in the visual deep learning process are repeatedly corrected.
7. The novel acromegaly screening method of claim 6, wherein: in the step (3), the artificial intelligence early screening system firstly cleans the data of the hand photo before performing artificial intelligence background measurement and calculation on the hand photo, rechecks and verifies the data of the hand photo, deletes repeated information, corrects errors and provides data consistency.
8. The novel acromegaly screening method of claim 5, wherein: in the step (3), the screening data can be used for a physical examination screening system, clinical effect observation, a knowledge base and early warning.
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