A novel machine learning model accurately screened for psychologic distress in patients with chronic rhinosinusitis using routine clinical variables.
Moxank Patel, Machine Learning Engineer at Meta, has worked across machine learning, information retrieval, NLP, computer vision, backend engineering and produc ...
9don MSN
Indian-origin sixth-grader trains machine-learning model to spot lithium deposits with 89% accuracy
Ishaan Dokania, a sixth-grader from Oregon, is exploring lithium resource identification using satellite imagery and machine ...
Machine learning (ML) is a foundational technology for modern AI, transforming the operational landscape of contemporary businesses. ML technology uses data to find patterns, spot anomalies and make ...
A machine learning model combining acoustic speech features with PHQ-9 responses improved depression screening accuracy in adolescents.
Quantum computers promise to solve problems that stump even the most powerful supercomputers, but the machines themselves are ...
Utilizing machine learning to assess distinct depressive symptoms improves the identification of adults with suicidal ideation.
Even if you explain 99% of the variance with PCA, your prediction accuracy might not improve by even 0.1%. This is one of the greatest tricks in statistics. Variance and predictive power are not as ...
A machine learning model utilizing longitudinal electronic diary data can accurately forecast the likelihood of next-day migraine attacks.
Experiments and machine learning reveal that grain boundary sliding governs the exceptional room-temperature ductility of an ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results