New algorithm identifies disease-linked changes in cells without prior training

A new algorithm could drive breakthroughs in understanding cancer, Alzheimer's disease and other potentially fatal conditions ...
DATAQUESTOpinion

India's semiconductor opportunity lies in AI-native design and sustainable innovation

The emerging convergence of AI-first design principles and environmental consciousness is reshaping how we think about ...
IEEE

Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions

Abstract: Malware has emerged as a cyber security threat that continuously changes to target computer systems, smart devices, and extensive networks with the development of information technologies.
Frontiers

Enhanced differentiation of breast lesions through integration of microvascular flow imaging and machine learning algorithms

Breast cancer diagnosis relies on imaging, yet conventional Doppler ultrasound possesses limitations in visualizing tumor microvasculature. This study aimed to compare Microvascular Flow imaging ...
IEEE

Comparison of Machine Learning Algorithms for Predicting Crime Hotspots

Abstract: Crime prediction is of great significance to the formulation of policing strategies and the implementation of crime prevention and control. Machine learning is the current mainstream ...
GitHub

Machine Learning project for classifying Iris flower species using Python and K-Nearest Neighbors (KNN).

This project uses Machine Learning to classify Iris flowers into three different species based on their physical measurements. The classification is performed using the K-Nearest Neighbors (KNN) ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
Frontiers

Research on predicting risk factors for re-bleeding in the acute phase of intracerebral hemorrhage using machine learning algorithms

Deng X, Xia J, Liang Z and Luo C (2026) Research on predicting risk factors for re-bleeding in the acute phase of intracerebral hemorrhage using machine learning algorithms.
Indianapolis RecorderOpinion

The algorithm doesn’t know you, but here’s how to make sure employers do

You've applied to dozens of jobs. Maybe hundreds. You've tailored your resume, followed up, and still heard nothing back. You ...