Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...
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Mistaken correlations: Why it's critical to move beyond overly aggregated machine-learning metrics
MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to ...
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.
Yale researchers have developed a machine learning model, called Immunostruct, that can help scientists create more ...
Machine learning models are usually complimented for their intelligence. However, their success mostly hinges on one fundamental aspect: data labeling for machine learning. A model has to get familiar ...
The severity of symptoms in posttraumatic stress disorder (PTSD) varies greatly across individuals in the first year after trauma and it remains difficult to predict whether someone might worsen, ...
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Machine learning model predicts serious transplant complications months before symptoms appear
A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications ...
Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average ...
Xanadu, a global leader in quantum computing software and quantum-photonic hardware, today announced a new research initiative with Lockheed Martin, the global defense and technology company, to ...
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