A machine learning lung cancer risk prediction model outperformed logistic regression, supporting improved risk assessment and more efficient radiology based lung cancer screening.
Researchers developed a machine learning model that could identify children in the ED who were at risk for developing sepsis ...
Patients’ financial resources affect their enrollment in oncology clinical trials to a greater degree than traditional ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Interesting Engineering on MSN
US researchers build fall-safe biped robots to advance real-world reinforcement learning
HybridLeg robots Olaf and Snogie use impact-safe design and self-recovery to enable scalable, real-world hardware ...
The presented findings are important for the field of cell-cycle control. They provide new insights into the origin of cell size variability in budding yeast. The strength of evidence is solid.
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