Then, we carried out real-time severe AKI prediction in the prospective validation study ... Comorbidity included hypertension, diabetes, cardiopathy, liver disease and malignant tumours. The primary ...

Mirza Khalid Baig, Assistant Professor, Biotechnology and Medical Engineering, has developed a new AI-driven approach to improve blood sugar predictions for people with diabetes. The findings of ...

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A web-based diabetes risk assessment system that uses machine learning ... a two-stage machine learning framework with Random Forest (ROC-AUC: 0.815) for accurate predictions.

As interpreted by SHAP, HbA1c, fasting glucose levels, duration of diabetes, and body mass index were identified as common key determinants influencing the model’s outcomes. Conclusion: The DR ...

Background: Diabetic retinopathy (DR) screening faces critical challenges in early detection due to its asymptomatic onset and the limitations of conventional prediction models. While existing studies ...

Diabetic Retinopathy and Glaucoma affected. Three feature relevance and sixteen classification Algorithms were analyzed and used to identify the contributing features that gave better prediction ...

The male and female prognostic models we developed and validated could be used to identify and target those most at risk of developing type 2 diabetes for referral to the NHS DPP. Implementation of ...

LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting and 2. An Effective Joint Prediction Model for Travel Demands and Traffic Flows.