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Machine learning uncovers early warning signs of depression in brain scans

A new computational model combined with brain imaging data reveals that relying too heavily on prior expectations when ...
BIOENGINEER

Quantum Machine Learning Edge Emerges in Predicting ICU Mortality From Electronic Health Records

A hybrid quantum-classical model outperformed XGBoost and other classical baselines in predicting ICU mortality across nearly ...
News Medical

Machine learning model can predict 28-day mortality in sepsis patients

Sepsis is one of the most common and lethal syndromes encountered in intensive care units (ICUs), and acute respiratory failure (ARF) represents one of its most critical complications. Once ...
ascopubs.org

Machine Learning Model for Predicting Severe Adverse Events in Oncology Patients Using the US Food and Drug Administration Adverse Event Reporting System

Cost-Effectiveness of Maintaining Higher Stem-Cell Collection Thresholds in the Chimeric Antigen Receptor T-Cell Era for Multiple Myeloma Predicting severe adverse events (SAEs) in oncology is ...
BIOENGINEER

Machine Learning Meets Ballistics: Predicting How PEEK Plates Deflect High-Speed Impacts

Researchers combined ballistic experiments, finite element modeling, and a neural network to predict how PEEK plates fail ...

[Part 3] Predicting Numbers or Choosing Categories?: A Gentle Explanation of Regression and Classification

Estimated reading time: approx. 3 minutes 30 secondsIn machine learning, models learned from past data are used to predict ...

Microsoft has a new machine learning tool to improve weather forecasts

Researchers with the company say they’ve found a new, cost-effective way to make more accurate weather forecasts two to six ...
Morningstar%2c Inc.

Machine Learning Can Forecast Which Stock Factors Will Outperform

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

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 learning. His project reached 89% accuracy in predicting potential lithium ...