Peru Amazon highway tied to 400% dengue surge within 5 kilometers of road

New roads bring changes to the regions they traverse. They can enable job opportunities, access to medicine and health care, ...

Using AI to provide new insights into why Ebola outcomes differ between patients

There is currently a serious outbreak in the Democratic Republic of the Congo of the severe and often fatal illness. Symptoms ...
RMD Open

Development and assessment of an assisted diagnosis model using machine learning for identifying adult-onset Still’s disease in fever of unknown origin: a retrospective …

Background Adult-onset Still’s disease (AOSD) is a systemic autoinflammatory disorder lacking a gold-standard diagnostic ...
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 ...

Objective: This study aimed to identify critical time points in SA-AKI progression development and validate dynamic, stratified machine learning prediction models for moderate-to-severe (Kidney ...
IEEE

Fuel Consumption Prediction Using Machine Learning: A Data-Driven Approach

Abstract: Accurately predicting fuel consumption is important for improving fuel efficiency, reducing costs, and lowering environmental impact. Traditional statistical methods struggle to understand ...
The New York Times

Prediction Markets’ Next Major Bet: Wall St. Traders

Platforms like Kalshi let millions wager on sports and pop culture. They’re now hoping institutions will use them for big-ticket trading like hedging. By Michael J. de la Merced Most people use ...
IEEE

An Explainable Machine Learning Framework for Dengue Disease Prediction Using MG-PSO

Abstract: Dengue fever, transmitted through Aedes mosquito bites, continues to escalate worldwide, placing disproportionate strain on tropical healthcare systems due to its capacity to progress into ...
Frontiers

Commentary: Awareness, use, attitudes, and implementation challenges of Bayesian dose prediction software in clinical practice: a multi-organizational survey

Alghanem et al. provide a timely assessment of the implementation landscape for Bayesian dose prediction software in clinical practice (Alghanem et al., 2026). Their survey shows that awareness among ...