The framework predicts how proteins will function with several interacting mutations and finds combinations that work well ...
Use the vitals package with ellmer to evaluate and compare the accuracy of LLMs, including writing evals to test local models.
Abstract: Malware poses a significant threat to network and information system security, particularly in industrial Internet of Things (IIoT) environments, where embedded systems and edge devices ...
Setting aside time in the school day to teach students social-emotional skills, such as emotional regulation and perspective-taking, can substantially boost students’ grade-point averages and ...
In a college-entrance-exam landscape long dominated by the SAT and the ACT, a relative newcomer has started to gain traction—especially in red states. The Classic Learning Test, first unveiled a ...
Background: The diagnosis of attention deficit hyperactivity disorder (ADHD) relies on comprehensive approaches, including clinical interviews, scales, and neuropsychological assessments. However, the ...
Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...
Abstract: To design the frequency selective surface (FSS) with more degrees of freedom (DoFs) and incident angle stability, an improved machine learning-based inverse topological design model is ...
A new article outlines a new tool that measures blood inflammation as a marker for poor CAR T therapy outcomes. Researchers with City of Hope, one of the largest and most advanced cancer research and ...
MCED tests utilize liquid biopsies to detect multiple cancer types early, using ctDNA and other biomarkers analyzed by machine learning. Machine learning models, including deep learning, enhance MCED ...
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