InfoWorld

A brief history of AI

Artificial intelligence has taken many forms over the years and is still evolving. Will machines soon surpass human knowledge and understanding?
European Medical Journal

Machine Learning Aids Diagnosis of Interstitial Pneumonia

Machine learning model accurately diagnoses interstitial pneumonia, matching pulmonologist expertise and predicting mortality risk.
Hosted on MSN

Wearables flag early heart failure via AI pattern recognition

Wearable technology has seamlessly integrated into our everyday lives, offering convenience and critical health insights. Recent advancements in artificial intelligence (AI) have equipped these ...
The New York Times

He’s big. He’s slow. And now he’s making stolen base history. What happened?

Josh Naylor is one of the biggest, slowest players in Major League Baseball. And out of nowhere, he’s become one of the game’s most prolific base stealers. In the past month, Naylor’s swiped 11 bags, ...
C&EN

Machine Learning-Assisted Recognition of Environmental Sulfur-Containing Chemicals in Nontargeted Mass Spectrometry Analysis of Inadequate Mass Resolution

Department of Chemistry, Faculty of Science, University of British Columbia, Vancouver Campus, 2036 Main Mall, Vancouver, British Columbia V6T 1Z1, Canada ...
Frontiers

Predicting visual acuity of treated ocular trauma based on pattern visual evoked potentials by machine learning models

Purpose: To develop effective machine learning models that analyze pattern visual evoked potentials (PVEPs) to predict the stabilized visual acuity (VA) of patients with treated ocular trauma. Methods ...
Frontiers

A hybrid approach for pattern recognition and interpretation in age-related false memory

Introduction: Aging is associated with a decline in essential cognitive functions such as language processing, memory, and attention, which significantly impacts the quality of life in later years.
IEEE

Enhanced Dual-Pattern Matching with Vision-Language Representation for out-of-Distribution Detection

Abstract: Out-of-distribution (OOD) detection presents a significant challenge in deploying pattern recognition and machine learning models, as they frequently fail to generalize to data from unseen ...
Scientific Research Publishing

Bishop, C. (2006) Pattern Recognition and Machine Learning. Springer.

ABSTRACT: This study presents a comparative analysis of machine learning models for threat detection in Internet of Things (IoT) devices using the CICIoT2023 dataset. We evaluate Logistic Regression, ...
IEEE

Improving Unimodal sEMG-Based Pattern Recognition Through Multimodal Generative Adversarial Learning

Abstract: Surface electromyography (sEMG)-based pattern recognition system is a kind of instrumentation and measurement system that captures, processes, and recognizes bioelectrical signals, like ...
C&EN

Unsupervised Machine Learning-Based Image Recognition of Raw Infrared Spectra: Toward Chemist-like Chemical Structural Classification and Beyond Numerical Data

Recent advances in artificial intelligence have significantly improved spectral data analysis. In this study, we used unsupervised machine learning to classify chemical compounds based on infrared (IR ...