Technology Networks

AI and Machine Learning in High-Throughput Screening

Explore how AI in high-throughput screening improves drug discovery through advanced data analysis, hit identification and ...
IEEE

The Impact of Feature Scaling in Machine Learning: Effects on Regression and Classification Tasks

Abstract: This study addresses the lack of comprehensive evaluations of feature scaling by systematically assessing 12 techniques, including less common methods such as VAST and Pareto, in 14 machine ...
The Lancet

Risk-stratified classification of pulmonary nodule malignancy via a machine learning model integrating imaging and cell-free DNA: a model development and validation study ...

aDepartment of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for ...
Frontiers

VAE deep learning model with domain adaptation, transfer learning and harmonization for diagnostic classification from multi-site neuroimaging data

The acquisition sites include: CALTECH, California Institute of Technology; CMU, Carnegie Mellon University; KKI, Kennedy Krieger Institute; LEUVEN, University of Leuven; MAX, Ludwig Maximilians ...
Journal of Medical Internet Research

Exploring the Perspectives of Pediatric Health Care Providers, Youth Patients, and Caregivers on Machine Learning Suicide Risk Classification: Mixed Methods Study

Exploring the Perspectives of Pediatric Health Care Providers, Youth Patients, and Caregivers on Machine Learning Suicide Risk Classification: Mixed Methods Study ...
Scientific Research Publishing

Allam, H., Makubvure, L., Gyamfi, B., Graham, K. and Akinwolere, K. (2025) Text Classification: How Machine Learning Is Revolutionizing Text Categorization. Information, 16, 130.

ABSTRACT: Pregnancy presents a unique clinical scenario where the safety of pharmacological interventions is of paramount importance. The potential teratogenic risks associated with drug intake during ...
sei.cmu

Practical Supervised Machine Learning Classification of Highly Imbalanced Text

In this paper, Austin Whisnant describes a machine learning model used to build a corpus of insider threat data to support insider threat research. As the insider threat problem grows and becomes more ...