Medical Xpress

Machine learning can predict patients' responses to antidepressants—while disentangling drug and placebo effects

Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global population. It is characterized by a persistent low mood, disruptions in typical ...
Frontiers

Explainable machine learning for stroke risk prediction: a comparative study with SHAP-based interpretation

Background: Stroke is one of the leading causes of death and disability worldwide, making early screening and risk prediction crucial. Traditional methods have limitations in handling nonlinear ...
Techno-Science.net

Flow Launcher: A Powerful Windows Launcher You Aren’t Using

Flow Launcher is a Start menu replacement for your Windows PC that lets you perform various system tasks more efficiently. You can think of it as a Spotlight Search for Windows, but with improved ...
International Monetary Fund

Nowcasting GCC GDP: A Machine Learning Solution for Enhanced Non-Oil GDP Prediction

This paper presents a machine learning–based nowcasting framework for estimating quarterly non-oil GDP growth in the Gulf Cooperation Council (GCC) countries. Leveraging machine learning models ...
IEEE

Computerized Automation and Machine Learning for Prediction of Melt Mass-Flow Rate Using Custom-Built Machine in Industrial IoT

Abstract: In the polymer industry, where polymers are transformed into a wide range of plastic products, accurate quality assessment through melt flow testing remains critical but challenging.
IEEE

Multivariate Machine Learning Model Based on YOLOv8 for Traffic Flow Prediction in Intelligent Transportation Systems

Abstract: Traffic flow prediction plays a crucial role in Intelligent Transportation Systems (ITS), as it substantially enhances traffic management efficiency, alleviates congestion, and improves road ...
ascopubs.org

Machine Learning Designed for Any Hematologic Flow Cytometry Data Set

Flow cytometry is a key diagnostic technique in hematology that provides protein information at a single-cell level. Traditionally interpreted manually in a sequence of two-dimensional plots, ...
Rochester Institute of Technology

RIT researchers use machine learning to better understand the pathways of disease

Cancer, Alzheimer’s, and other diseases follow a pathway in the human body. It starts at the molecular and cellular levels, and through a series of complex interactions can lead to the development and ...
Journal of Medical Internet Research

Prediction of Moderate-to-Severe Sepsis-Associated Acute Kidney Injury Using a Dual-Timepoint Machine Learning Model: Development, Multiregional Validation, and Clinical ...

Prediction of Moderate-to-Severe Sepsis-Associated Acute Kidney Injury Using a Dual-Timepoint Machine Learning Model: Development, Multiregional Validation, and Clinical Deployment Study ...
YDR

The Penn State football 2025 season-opening depth chart: Our prediction vs Nevada

Penn State football is about to launch its most highly anticipated season in more than 25 years. That No. 3 preseason ranking is supported by the premium construction of coach James Franklin's team ― ...
The New York Times

Knicks’ predictions: Way-too-early depth chart surprises, rotations and starting lineup changes

While the bulk of the New York Knicks’ roster is set for the start of the 2025-26 season, the team still has some loose ends to tie up before the start of the season. After signing Jordan Clarkson and ...
Scientific Research Publishing

Xie, P., Li, T., Liu, J., Du, S., Yang, X. and Zhang, J. (2020) Urban Flow Prediction from Spatiotemporal Data Using Machine Learning: A Survey. Information Fusion, 59, 1-12.

ABSTRACT: Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction ...