Rochester Institute of Technology

Researchers develop new method for predicting chaos

RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.

Fentanyl or phony? Machine learning algorithm learns to pick out opioid signatures

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...
University of Birmingham

Machine‑learning framework could transform prediction of drug side effects

Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.
eCampus News

Citing the machine: When and how to acknowledge AI use in academic work

Institutions should embed an AI use framework into syllabi, program handbooks, IRB protocols, and dissertation templates.
The Lancet

Machine learning prediction of 1-year mortality in older patients with heart failure: a nationwide, multicenter, prospective cohort study

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
FinanceFeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Homewood’s Maple Tree Inn faced a fire and three location changes. Last year, it celebrated 50 years.

Katie and Erich Wennberg have gone through trials and tribulations while working at the Maple Tree Inn. The restaurant’s 50th anniversary wasn’t easy to achieve.
IEEE

Hybrid Tree-Based Machine Learning Models for State-of-Charge and Core Temperature Estimation in EV Batteries

Abstract: Accurate estimation of State-of-Charge (SoC) and core temperature is fundamental to optimizing the performance, safety, and longevity of Lithium-Ion Batteries (LiBs), particularly in ...
BMJ Open

Generating actionable insights to support point-of-care suicide risk decision-making in a safety-net healthcare system: a machine learning approach to predicting dynamic risk ...

Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...
Frontiers

Clinical decision system for renal cell carcinoma integrating interpretable machine learning algorithms

Background: Kidney cancer is a highly heterogeneous oncologic disease with historically poor prognosis. Precise assessment of the risk of distal metastasis can facilitate risk stratification and ...
Morningstar

A First-of-Its-Kind, Formula-Free Guide to AI and Machine Learning for Decision Makers, by Corina J. Shtir, PhD

SAN DIEGO, Nov. 18, 2025 /PRNewswire/ -- AI and Machine Learning Unpacked: A Practical Guide for Decision Makers in Life Sciences and Healthcare by Corina J. Shtir ...
Frontiers

Development of a machine learning-based predictive model for osteoporosis risk and its application in clinical decision support

1 Jiangxi University of Chinese Medicine, Nanchang, Jiangxi, China 2 Affiliated Hospital of Jiangxi University of Chinese Medicine, Nanchang, Jiangxi, China Objective: This study was aimed at ...