APPLICATION OF ARTIFICIAL INTELLIGENCE (AI) ALGORITHMS IN DISEASE DIAGNOSIS
AI algorithms have the ability to analyze clinical and medical imaging data, helping to identify pathological signs and support physicians in the diagnostic process. The application of AI enables us to
- Analyze medical imaging such as X-rays, CT scans, MRI, and ultrasound. Deep learning algorithms can learn to recognize pathological signs in images and provide automated assessments of tumors and lesions. Based on clinical data, symptoms, and test results, AI systems can provide initial diagnostic suggestions, regarding the patient's condition.
- Predict disease status and patient response based on clinical data and previous treatment history. This helps physicians develop optimal treatment plans and forecast the patient's future condition.
Precision Med applies AI to disease diagnosis in EHR, providing users with
- More accurate disease diagnosis
- Increased efficiency in disease diagnosis
- Prediction and prevention based on medical history and genetic information
- Support for clinical decision-making and selection of the best treatment approach for each patient
Below is an illustration of the application of AI algorithms is diagnosing heart disease.
The report consists of two columns representing information:
- The left column: Based on the condition of each surveyor factor, the AI algorithm determines the probability of the person having the disease to be 91.8%. This result is presented in the left-hand column. According to the American Heart Association, the surveyed individual belongs to a high-risk group of the disease.
- The right column of the image (the top half in black and the bottom half in yellow) describes the value of risk factors related to the disease, such as age, gender, chest pain location (cp), etc.
- A list of factors impacting the disease incidence rate is listed in descending order from high to low.