Among patients with chronic noncancer pain, a novel machine learning model effectively predicts opioid use disorder risk.
Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global population. It is characterized by a persistent low mood, disruptions in typical ...
Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
A new and important discovery comes from the field of oncological research thanks to the joint work of researchers from the Sbarro Institute in Philadelphia, the National Cancer Institute – Pascale ...
A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
A new long-term prediction tool estimates the risk of dying from prostate cancer, offering a more accurate way to interpret prostate-specific antigen (PSA) test results compared to existing models.
New research shows supervised machine learning models combining Helicobacter pylori genomic data with patient demographics can accurately predict gastric cancer risk.
In the evolving landscape of oncology, skin cancer diagnosis stands out as a domain where the synergy between AI and multimodal imaging is rapidly changing ...
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