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 ...

Recursion, Schrödinger Building, Oxford Science Park, Oxford OX4 4GE, U.K. Exscientia, Schrödinger Building, Oxford Science Park, Oxford OX4 4GE, U.K. Recursion ...

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 ...

bash_unit allows you to write unit tests (functions starting with test), run them and, in case of failure, displays the stack trace with source file and line number indications to locate the problem.

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 ...

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 ...

aDepartment of Anesthesiology and Pain Medicine, Seoul National University College of Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea bVUNO, 479 ...

VML introduces a new framework of machine learning. Unlike conventional machine learning models that are typically optimized over a continuous parameter space, VML constrains the parameter space to be ...

Abstract: This study explores the intersection of self-esteem assessment, specific learning disorders (SLDs), and emerging technologies, particularly virtual reality (VR) and machine learning (ML).