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

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 successful application of large-scale transformer models in Natural Language Processing (NLP) is often hindered by the substantial computational cost and data requirements of full fine-tuning.

Abstract: Large amounts of digital data are produced daily through society’s use of government and private companies. Digital transformation contributes to the increasing amount of structured and ...

Text classification plays a critical role in numerous natural language processing applications, yet limited work has addressed the unique linguistic structure of African languages such as Kiswahili.

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

Chronic Coronary Disease (CCD) is a leading global cause of morbidity and mortality. Existing Pre-test Probability (PTP) models mainly rely on in-hospital data and clinician judgment. This study aims ...

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