The Francis College of Engineering, Department of Electrical and Computer Engineering, invites you to attend a Doctoral Dissertation Proposal defense by Masoumeh Farhadi Nia on: "Machine Learning for ...

Machine learning models using initial neuropsychological and neuropsychiatric clinical data accurately distinguished AD from bvFTD.

An analysis of 5 machine-learning algorithms identified predictors for moderate-to-severe cancer-related fatigue in patients with CRC undergoing chemotherapy.

DenseWolf-K, a hybrid AI framework, achieved 99.64% accuracy in brain tumour MRI classification, revolutionising medical ...

Groundwater quality in Kasganj is critically compromised. This study uses advanced machine learning to predict contamination ...

Explainable AI was particularly valuable in validating the predictions. The Grad-CAM and Class Activation Mapping methods ...

Machine learning is transforming how crypto traders create and understand signals. From supervised models such as Random Forests and Gradient Boosting Machines to sophisticated deep learning hybrids ...

Despite differing regulatory philosophies, all regions recognize AI’s value in transactional transparency, anomaly detection, and early fraud prevention. The study identifies a clear shift from manual ...

A six-metabolite plasma panel was developed and validated for gastric cancer (GC) diagnosis using UPLC-MS and machine ...

Explore how artificial intelligence and digital innovations are transforming sludge dewatering in wastewater systems, ...