- An AI system developed by the Japanese Institute of Oncology;
- It is used for diagnosing lung cancer, breast cancer, and COVID-19 viral pneumonia.
- The system's sensitivity exceeds 90%, which allows for a 15% improvement in early cancer detection.
- In the Almaty region, the implementation of the AI system led to an 11% increase in the detection of pathologies.
- Data Collection and Training
2. Medical Image Analysis
- Image Preprocessing: AI enhances image quality, removes noise, and increases contrast.
- Feature Extraction: AI analyzes tissue structures and density to identify anomalies such as nodules or shadows indicating tumors.
- Contour and Texture Analysis: AI determines the shape, boundaries, and density of formations to differentiate malignant tumors from benign ones.
- Structural Analysis: Based on CT and MRI data, AI assesses the likelihood of malignancy.
- AI evaluates the probability of malignancy (e.g., "85% likelihood of malignancy"). It highlights suspicious areas, helping the doctor focus on critical details.
- AI evaluates the probability of malignancy (e.g., "85% likelihood of malignancy"). It highlights suspicious areas, helping the doctor focus on critical details.
- The system continuously improves by receiving feedback from doctors. This allows the AI to enhance its accuracy and efficiency with each new case.
- Analysis Speed: AI can process a vast number of images in just minutes, significantly accelerating the diagnostic process.
- High Accuracy: Modern AI systems achieve accuracy rates of over 90%, sometimes surpassing human diagnostics in several parameters.
- Early Diagnosis: AI can detect minimal changes that may be missed during visual inspections, increasing the chances of successful treatment.
- Reduced Burden on Doctors: AI handles the routine task of image analysis, allowing doctors to focus on making critical clinical decisions.
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