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This Wired article explores how AI could help detect fatty liver disease earlier by analyzing electronic health records and lab reports, potentially enabling prevention and reversal of liver damage.
AI-powered early warning systems using infrared sensors and drones are being deployed in India to reduce deadly clashes between humans and wild elephants.
This study develops an XGBoost classifier using SHAP explainability on eight clinical biomarkers from the ADNI dataset to achieve three-class Alzheimer's disease detection (normal cognition, MCI, AD), reaching a macro AUC of 0.982 and Cohen's kappa of 0.909 on the held-out test set. SHAP analysis identifies CDR Global as the dominant predictor for NC and MCI, while CDR-SB and MMSE together drive AD classification.
A new AI model (REDMOD) can detect pancreatic cancer up to three years earlier than human doctors by analyzing CT scans for subtle irregularities, potentially improving early diagnosis and survival rates.