At Florida International University, researchers are harnessing the power of AI and sound to revolutionize how we detect cardiovascular disease.

For employers, earlier detection can influence costs, productivity and how significantly a serious diagnosis can affect an ...

Hyderabad researchers develop a patented AI system with 96 per cent accuracy to detect plant leaf diseases and recommend ...

Detecting sub-5nm defects creates huge challenges for chipmakers, challenges that have a direct impact on yield, reliability, and profitability. In addition to being smaller and harder to detect, ...

Researchers have developed an AI-powered leaf disease detection system with 96% accuracy, enabling early identification and treatment to prevent significant yield losses.

Materials scientists at Rice University have developed a new workflow methodology for measuring microscopic defects in diamond and other advanced semiconductor materials. By making it easier to spot ...

A study explores how AI and ML can improve early detection of neurological diseases, including Parkinson’s disease, ...

Researchers have designed a robust image-based anomaly detection (AD) framework with illumination enhancement and noise suppression features that can enhance the detection of subtle defects in ...

Detecting macro-defects early in the wafer processing flow is vital for yield and process improvement, and it is driving innovations in both inspection techniques and wafer test map analysis. At the ...

Congenital heart defects (abnormalities of the heart that are present at birth) are the most common type of birth defect and, according to the Centers for Disease Control and Prevention, about 1 in 4 ...