Frontiers

Advances in machine and deep learning for ECG beat classification: a systematic review

The electrocardiogram (ECG) is an important tool for exploring the structure and function of the heart due to its low cost, ease of use, efficiency, and non-invasive nature. With the rapid development ...
IEEE

An ECG Data Feature Selection Comparison: Machine Learning and Expert Doctors

The ECG signals analysis is a frequently used approach for classification of cardiac patients. Traditionally, this analysis is made by expert doctors. However, recently, it is increasingly supported ...
PC Gamer

Arc Raiders' use of AI highlights the tension and confusion over where machine learning ends and generative AI begins

Like Embark Studios' 2023 shooter The Finals, its new game Arc Raiders, out today, comes bearing an "AI generated content disclosure" on its Steam page. "During the development process, we may use ...
National Academies of Sciences%2c Engineering%2c and Medicine

Making Machine Learning Safer in High-Stakes Settings

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...
Targeted Oncology

Machine Learning Model May Optimize Treatment Selection and Survival in HCC

The ML model stratifies HCC patients by mortality risk, guiding treatment decisions between liver transplantation and surgical resection. The model demonstrated improved survival outcomes, with a 54% ...
TechCrunch

Google is experimenting with machine learning-powered age-estimation tech in the US

Google is testing a machine learning-powered tech in the U.S. to determine the age of users and filter content across all its products accordingly. The company said it will consider data from Google ...
Live Science

Scientists use quantum machine learning to create semiconductors for the first time – and it could transform how chips are made

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing. When you purchase through ...
Frontiers

Advancing cardiac diagnostics: high-accuracy arrhythmia classification with the EGOLF-net model

Introduction: Arrhythmia, characterized by irregular heartbeats, can range from harmless to potentially life-threatening disturbances in heart rhythm. Effective detection and classification of ...
IEEE

FSHOADC - Feature Selection and Hyperparameter Optimization Based Arrhythmia Detection and Classification: A Machine Learning Approach for Arrhythmia Detection using ECG Signals

Abstract: One essential and often used tool for the diagnosis of cardiovascular disorders is the electrocardiogram (ECG). With the emergence of artificial intelligence (AI), it is possible to have ...
News Medical

Machine learning model guides smarter gene selection in newborn screening

More than a decade ago, researchers launched the BabySeq Project, a pilot program to return newborn genomic sequencing results to parents and measure the effects on newborn care. Today, over 30 ...
Science Daily

Researchers use machine learning to engineer 'bespoke enzymes' for gene editing

Genome editing has advanced at a rapid pace with promising results for treating genetic conditions -- but there is always room for improvement. A new paper showcases the power of scalable protein ...