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DiaDetectX is a deep learning-based diabetes risk assessment tool designed specifically for women. It not only provides risk predictions but also uses explainable AI technology to help users understand the medical basis behind the predictions, promoting early prevention and health management.
Section 01
DiaDetectX is a deep learning-based diabetes risk assessment tool designed specifically for women. Combining explainable AI technologies (such as SHAP and LIME), it not only provides risk prediction results but also explains the medical basis behind the predictions, helping users understand their own health status and promoting early prevention and personalized health management.
Section 02
Diabetes is a major global public health challenge. According to IDF statistics, over 500 million adults worldwide are affected. Women face unique risks such as gestational diabetes, PCOS, and menopausal hormone changes. Traditional screening relies on clinical experience and regular physical examinations, often leading to late detection and difficulty reversing the condition.
Section 03
Includes demographic data (age, BMI), physiological indicators (blood pressure, blood glucose), lifestyle, family medical history, and women-specific factors (pregnancy history, PCOS, menopausal status).
May use MLP, DNN, or ensemble learning methods, combined with batch normalization and Dropout to prevent overfitting.
Uses SHAP (feature contribution), LIME (local explanation), attention mechanisms, and visualization to present risk factors.
Section 04
Section 05
Based on a web application, including a responsive front-end (data input, result visualization), back-end inference API, and data security measures.
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