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AI for Predicting Resistance in Gram-Negative Bloodstream Infections: A New Frontier in Sepsis Management

AI for Predicting Resistance in Gram-Negative Bloodstream Infections: A New Frontier in Sepsis Management

Gram-negative bloodstream infections (GN-BSI) remain among the most severe and lethal infectious diseases, particularly in intensive care units and regions where multidrug resistance (MDR) is endemic.

AI for Predicting Resistance in Gram-Negative Bloodstream Infections: A New Frontier in Sepsis Management

Gram-negative bloodstream infections (GN-BSI) remain among the most severe and lethal infectious diseases, particularly in intensive care units and regions where multidrug resistance (MDR) is endemic.
Emerging Applications of Machine Learning and AI for Predictive Modeling in Precision Medicine

Emerging Applications of Machine Learning and AI for Predictive Modeling in Precision Medicine

As the availability of high-quality longitudinal datasets grows, AI’s ability to transform care from reactive to proactive will continue to expand—offering clinicians unprecedented tools for individualized patient management.

Emerging Applications of Machine Learning and AI for Predictive Modeling in Precision Medicine

As the availability of high-quality longitudinal datasets grows, AI’s ability to transform care from reactive to proactive will continue to expand—offering clinicians unprecedented tools for individualized patient management.
Multimodal AI in Digital Medicine: Toward a More Holistic Future of Healthcare

Multimodal AI in Digital Medicine: Toward a More Holistic Future of Healthcare

Multimodal artificial intelligence (AI) is redefining the future of digital medicine by integrating diverse data types—medical imaging, electronic health records (EHR), genomics, sensor data, and clinical narratives—into unified analytical models.

Multimodal AI in Digital Medicine: Toward a More Holistic Future of Healthcare

Multimodal artificial intelligence (AI) is redefining the future of digital medicine by integrating diverse data types—medical imaging, electronic health records (EHR), genomics, sensor data, and clinical narratives—into unified analytical models.