Background Although chest X-rays (CXRs) are widely used, diagnosing mitral stenosis (MS) based solely on CXR findings remains ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

From disaster zones to underground tunnels, robots are increasingly being sent where humans cannot safely go. But many of ...

Researchers in Slovakia have demonstrated a machine-learning framework that predicts PV inverter output and detects anomalies using only electrical and temporal data, achieving 100% accuracy in ...

Master’s thesis position (M.Sc. student) in Deep Learning for Healthcare.

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

Weeds pose the most persistent and costly threat to crop production in Canada, driving widespread herbicide use and accelerating the rise of herbicide-resistant species ...

Despite the excitement surrounding generative AI, the data shows that scientific research is still powered primarily by ...

Abstract: Electroluminescence (EL) imaging is the most widely used diagnostic technique for identifying flaws at every stage of the production, installation, and operation of solar modules. This ...

Researchers at Thomas Jefferson University have developed an automated machine learning (AutoML) model that can accurately differentiate between two common types of brain tumors using preoperative MRI ...

Researchers at Thomas Jefferson University have developed a groundbreaking automated machine learning (AutoML) model that can accurately differentiate between two common types of brain tumors using ...

Abstract: One of the important health concern all over the globe is Breast Cancer in women. It is a complex disease that requires a thorough diagnosis before treatment can begin. This research paper ...