An AI-powered model that analyzes electrocardiograms was able to accurately detect COPD early in internal testing and ...

A growing movement of technically sophisticated patients are channeling their diagnoses into AI systems that address gaps ...

The neural network approach uses multiple or “deep” layers that learn to identify increasingly complex features in data. The ...

Artificial intelligence (AI) electrocardiogram (ECG) data are promising for early detection of chronic obstructive pulmonary disease (COPD).

Md Firoz Kabir, a PhD researcher in Information Technology, is emerging as a leading voice in artificial intelligence-driven ...

AI in medical imaging market growth is driven by deep learning advancements, personalized medicine, lack of radiologists, and AI integration in telemedicine. It faces challenges like high costs, data ...

The proposed Coordinate-Aware Feature Excitation (CAFE) module and Position-Aware Upsampling (Pos-Up) module both adhere to ...

Regulations limit both the intensity and frequency of whip use during horse racing. Nevertheless, compliance is currently verified manually after each race. Researchers at University of Tsukuba have ...

Abstract: Image classification in datasets with a lot of variation is hard because of differences within classes and similarities between classes, which can lead to wrong classifications and less ...

Intrusion detection systems, long constrained by high false-positive rates and limited adaptability, are being re-engineered ...

Across all included studies, AI-based diagnostic systems demonstrated high overall accuracy. When measured against expert ...

A new forensic framework designed specifically for the Internet of Things (IoT) is discussed in the International Journal of ...