Nature

Development of machine learning models for gait-based classification of incomplete spinal cord injuries and cauda equina syndrome

Incomplete tetraplegia, incomplete paraplegia, and cauda equina syndrome are major neurological disorders that significantly reduce patients’ quality of life, primarily due to impaired motor function ...
Nature

Longitudinal modeling of Post-COVID-19 condition over three years: A machine learning approach using clinical, neuropsychological, and fluid markers

Post-COVID-19 condition (PCC) manifests with prolonged, heterogeneous symptoms challenging both, diagnosis and therapeutic management. This three-year longitudinal study analyzed data from 93 adults ...
ascopubs.org

Machine Learning Risk Stratification Approach Using Patient-Reported Outcomes for Forecasting Unplanned Health Care Use and Symptom Burden in Cancer Survivors

Effective risk stratification in cancer survivorship requires handling longitudinal data characterized by multimodal inputs, irregular follow-up, and recurrent clinical events. This study evaluated ...
News-Medical.Net

Researchers identify hidden self-harm histories using machine learning

Important mental health history is often present in medical records but hard to find, especially when it is missing from the diagnosis codes that clinicians, researchers and health systems use to ...
News Medical

Machine learning advances human-centric drug toxicity prediction

In the UK, there was a case where TGN1412, an immunotherapy under development, triggered a cytokine storm within hours of administration to humans, leading to multiple organ failure. Another example, ...