An artificial intelligence and genetic test based early diagnosis kit for osteoporosis

Abstract

The invention is related to the early detection of osteoporosis. In this context, the invention, utilizing genetic tests and artificial intelligence analysis, can determine the osteoporosis risk using individuals' genetic structures and clinical data. Early diagnosis allows for the initiation of treatment before the disease progresses and prevents potential complications.

Description

[0001] AN ARTIFICIAL INTELLIGENCE AND GENETIC TEST BASED EARLY DIAGNOSIS KIT FOR OSTEOPOROSIS

[0002] TECHNICAL FIELD

[0003] The invention relates to the early detection of osteoporosis. In this context, the invention, which uses genetic tests and artificial intelligence analysis, can determine the risk of osteoporosis by utilizing individuals' genetic makeup and clinical data. Early diagnosis allows for the initiation of treatment before the disease progresses and prevents possible complications.

[0004] BACKGROUND

[0005] With the increasing life expectancy today, the elderly population and the health issues it brings along are also gaining importance. Along with extended life spans, osteoporosis has become a significant public health problem in many parts of the world. Recent studies have shown the role of race and ethnicity, age, and a positive family history in osteoporosis.

[0006] When we look at the global digital health market as a whole, including software, hardware, and services, we see that the market, which was valued at $86 billion in 2015, reached a size of $192 billion in 2020, and is estimated to be $505 billion by 2025. The global digital health services market size is expected to reach $278.3 billion by 2027. Turkey is already in a growing market position for medical technologies and healthcare services. The total market size in Turkey is expected to reach $2.13 billion by 2027, with digital health revenue in 2022 expected to be $1.16 billion.

[0007] In the United States, 1.5 million fractures occur annually due to osteoporosis. These include 300,000 hip fractures, 700,000 vertebral fractures, 250,000 wrist fractures, and 300,000 other fractures. Approximately 20% of those with a hip fracture die within the first year, and more than 30% become disabled. Lifetime risk of death for women aged 50 and postmenopausal: coronary heart disease 31.0%, hip fracture 2.8%, breast cancer 2.8%, and uterine cancer 0.7%.

[0008] Globally, the number of hip fractures was 1.7 million in the 1990s and is expected to reach 6.3 million by 2050. According to the International Osteoporosis Foundation, a fracture caused by osteoporosis occurs every three seconds worldwide, and one in three women and one in five men over the age of 50 will experience an osteoporosis-related fracture.

[0009] The most significant consequence of osteoporosis is fractures and the resulting disabilities. The risk of hip, vertebral, and wrist fractures is considered to be 40% in women and 13% in men over the age of 50. These statistical data reveal that 4 out of every 10 patients over the age of 50 are at risk of encountering a hip, vertebral, or wrist fracture. When looking at the costs and social aspects of fractures, major problems arise. It is known that 1 .5 million fractures occur annually in the USA, with 300,000 hip, 700,000 vertebral, 250,000 wrist, and 300,000 other fractures. 20% of patients exposed to a hip fracture, unfortunately, die within the first year, and more than 30% become disabled. The number of hip fractures, which was 1 .7 million at the beginning of the 1990s, is estimated to rise to 6.5 million by 2050.

[0010] In the current state of technology, early diagnosis of osteoporosis is based on clinical evaluations, radiological examinations, and densitometry tests that measure bone mineral density. Some of these traditional methods include:

[0011] Clinical Evaluation: Doctors assess patients' medical history and conduct physical exams to identify osteoporosis risk factors. However, this method can make early diagnosis difficult since the disease often does not show symptoms in its early stages.

[0012] Densitometry Tests: Densitometry is a type of radiological test that measures bone mineral density. Methods like DXA (Dual-Energy X-ray Absorptiometry) are used to measure bone density and are widely used to assess the risk of osteoporosis.

[0013] Blood Tests: Blood tests can be used to measure markers related to bone metabolism. For example, certain biochemical markers in the blood can be examined as indicators of bone formation and breakdown processes.

[0014] The diagnostic kit in question combines genetic testing and artificial intelligence analysis to offer a more specific and early diagnosis opportunity. Genetic tests can help assess individuals' genetic predispositions, while artificial intelligence can evaluate large datasets to produce more accurate and personalized results. This could allow for intervention in the early stages of the disease and optimize treatment processes. AIM OF THE INVENTION

[0015] The kit subject to the invention includes genetic tests aimed at determining individuals' genetic predispositions. One purpose of the invention is to better understand the risk of developing osteoporosis and to suggest personalized health measures for individuals. Another purpose is to use artificial intelligence analysis to evaluate individuals' clinical data and suggest personalized treatment strategies. This provides more effective treatment by considering the specific characteristics of the disease.

[0016] Artificial intelligence is also used to monitor patients' responses to treatment and the progression of the disease. This can assist healthcare professionals by providing continuous updated information about patients' conditions, helping in adjusting treatment plans.

[0017] The diagnostic kit containing artificial intelligence and genetic tests falls within the medical technology or medical devices sector. This sector focuses on advanced technologies used for the diagnosis and treatment of diseases.

[0018] Genetic tests represent a significant component in the field of biotechnology, focusing on the manipulation, analysis, and development of technology for biomedical applications. Artificial intelligence plays a crucial role in the health technology sector, which is focused on using technology to improve healthcare services, and to diagnose and treat diseases early.

[0019] DETAILED DESCRIPTION OF THE INVENTION

[0020] The invention concerns a kit containing software with a specialized algorithm created through artificial intelligence and genetic tests to analyze individuals' genetic structure and predict their risk of developing osteoporosis. The invention provides approximately a 10% improvement in the rate of early diagnosis for individuals at risk of osteoporosis. Trials conducted with our invention on 100 patients have achieved an accuracy rate of over 85%. The invention has also reduced the ability of individuals with osteoporosis to decrease fracture rates by approximately 14%. Positive feedback from patients has been calculated at about 40%. Moreover, our invention has prevented approximately 25% in cost losses thanks to early diagnosis. Additionally, compared to conventional methods, our invention has sped up the early diagnosis of osteoporosis by 20%. The most significant advantage provided by the invention is the ability to detect symptoms before the disease develops, allowing for earlier initiation of treatment processes. Quick diagnosis is important to prevent the progression of osteoporosis and reduce the risk of complications.

[0021] The genetic tests included in the content of the diagnostic kit subject to the invention assess the risk of osteoporosis by analyzing individuals' genetic structure. The software containing artificial intelligence uses genetic data and other clinical information to offer a personalized approach. Thus, more personalized prevention and treatment plans are created for individuals. The mentioned artificial intelligence algorithm is housed in any electronic device containing a processor capable of loading software. Therefore, the hardware included in the invention is any electronic device that contains a processor capable of loading software containing the artificial intelligence algorithm. This electronic device could be a computer, mobile phone, tablet, or any similar electronic device.

[0022] The software algorithm containing artificial intelligence can analyze large data sets to identify osteoporosis risk factors and symptoms. These analyses can determine factors important for the development of osteoporosis and be used to predict future risks. Thus, it provides a valuable tool for monitoring patients' conditions and predicting potential complications.

[0023] The features of the artificial intelligence algorithm within the software in the electronic device are as follows:

[0024] It uses Python's numpy and keras libraries. Keras is a high-level neural networks library written in Python, open-source, and can be run on Theano, CNTK, or TensorFlow. Development has been carried out in the Visual Studio Code environment. A database setup has been provided, and information is stored in a PostgreSQL environment.

[0025] Diagnosis and inference with the kit subject to the invention are carried out as described in this section. Initially, traditional bone density tests to be analyzed by artificial intelligence are conducted on the patient. The evaluation of these tests by artificial intelligence offers a different approach for early diagnosis in osteoporosis compared to traditional bone density tests. Bone density tests are conducted in the BMP4, BMP6, and RUNX2 SNP (single nucleotide polymorphisms) regions. The novelty of the invention is the first-time consideration of these SNP regions. Apart from bone density tests, genetic tests are also applied to patients, analyzing individuals' genetic structure to help predict certain disease risks. Blood is drawn from the person to be analyzed for DNA analysis, and primer pairs suitable for the exons determined for the BMP4, BMP6, and RUNX2 genes are amplified with PCR. Mutation / polymorphism analysis uses the Sanger DNA Sequencing Technique to detect possible mutations and polymorphisms in the genes coding for target proteins in the osteogenic signaling pathway in the study and control group patients, and the results are analyzed with Chromas DNA Sequencing Software. Mutations are analyzed using the PolyPhen-2 bioinformatics tool for pathogenic predictions on bone healing.

[0026] The device containing the software with artificial intelligence algorithms analyzes genetic data and helps predict osteoporosis risk. The logic here is generally to predict disease risks or monitor health conditions by evaluating genetic data and other health data. The mentioned artificial intelligence model is called a "Multi-Layer Feedforward Artificial Neural Network." Autoencoders are used in the learning part of the artificial intelligence model.

[0027] Within the software content in the device, scores corresponding to previously determined problematic and unproblematic structures are found. The genetic analysis results of the patient to be evaluated are scored by the software according to these predetermined scores. This scoring measures the probability of healing for the patient's bone fractures and makes an inference. With each measurement made, machine learning occurs with autoencoders in accordance with the feedback from the doctor who is following up and requested the measurement. That is, scores are revised by artificial intelligence for the next evaluations based on the accuracy of each evaluation. The data inputs of the patient to be evaluated by the artificial intelligence within the software in the device are listed below:

[0028] General information

[0029] 1.Age

[0030] 2. Gender

[0031] 3. Menopause status

[0032] 4. Number of pregnancies

[0033] 5. Osteoporosis in the family

[0034] 10-Question Test

[0035] 6. Did any of your family members experience a hip fracture after a mild bump or fall?

[0036] 7. Have you experienced a fracture in any bone after a mild bump or fall?

[0037] 8. Have you used corticosteroids (cortisone, prednisone, etc.) for more than three months? 9. Have you experienced a height loss of more than three centimeters?

[0038] 10. Do you regularly consume alcohol?

[0039] 11.Do you smoke more than 20 cigarettes a day?

[0040] 12. Do you frequently have diarrhea?

[0041] 13. Did you enter menopause before the age of 45?

[0042] 14. Have you had periods of amenorrhea (no menstruation) for 12 months or longer due to reasons other than pregnancy or menopause?

[0043] 15. Have you experienced impotence or loss of libido due to decreased testosterone levels?

[0044] Blood Test

[0045] 16. Calcium

[0046] 1 / .Phosphorus

[0047] 18.Alkaline Phosphatase

[0048] 19.Vitamin D

[0049] 20. Parathyroid Hormone

[0050] 21.TSH

[0051] 22. Estrogen

[0052] 23.Testosterone

Claims

CLAIMS1 . An early diagnosis diagnostic kit for osteoporosis with artificial intelligence and genetic testing, characterized by comprising;- An electronic device containing a processor capable of installing a software,- A software analyzing bone density tests and blood tests conducted in the BMP4, BMP6, and RUNX2 SNP (single nucleotide polymorphisms) regions, scoring the results of bone density tests and blood tests within the framework of scores corresponding to previously determined problematic and unproblematic structures, and using autoencoders in the learning part, a "Multi-Layer Feedforward Artificial Neural Network" artificial intelligence model that measures and infers the healing probability of the patient's bone fractures, with machine learning occurring with each measurement made in accordance with the feedback from the doctor who is following up and requested the measurement.