Machine learning model predicts serious transplant complications months before symptoms appear

A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications after stem cell and bone marrow transplants, according to new research ...
News-Medical.Net

Machine learning model demonstrates insulin resistance as a risk factor for 12 types of cancer

Insulin resistance - when the body doesn't properly respond to insulin, a hormone that helps control blood glucose levels - ...
IEEE

Predictive Modeling of Employee Attrition Using Tree-Based Machine Learning Classifiers

Abstract: Employee attrition poses considerable challenges for organizations by affecting productivity and increasing recruitment costs. This study employs tree-based machine learning classifiers to ...
The Southern Maryland Chronicle on MSN

How are QA teams using machine learning to predict test failures in real time?

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

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.
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 ...
BMJ

Development of an interpretable machine learning model for frailty risk prediction in older adult care institutions: a mixed-methods, cross-sectional study in China

Objective To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced ...
IEEE

A Three-Stage Decision-Making Method Based on Machine Learning for Preventive Maintenance of Airport Pavement

Abstract: The goal of preventative maintenance (PM) decision-making on airport pavements is to deploy the appropriate maintenance countermeasures at the correct time. This paper proposed a three-stage ...
Visual Studio Magazine

Decision Tree Regression from Scratch with Pointers Using C#

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...
marktechpost

How to Build an Agentic Decision-Tree RAG System with Intelligent Query Routing, Self-Checking, and Iterative Refinement?

In this tutorial, we build an advanced Agentic Retrieval-Augmented Generation (RAG) system that goes beyond simple question answering. We design it to intelligently route queries to the right ...