A machine learning-driven eNose detects ovarian cancer in blood plasma with 97 % sensitivity and specificity, offering a promising biomarker-agnostic approach.

A new machine learning model built using a simple and interpretable approach predicts in-hospital death in patients with acute liver failure and reveals top risk drivers.

A study published in The Journal of Engineering Research at Sultan Qaboos University presents an advanced intrusion detection system (IDS) designed to improve the accuracy and efficiency of ...

This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...

A new study published in the journal Minerals sheds light on this sweeping shift. Titled Big Data and AI in Geoscience: From ...

Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

Read more about AI-driven air quality system promises faster, more reliable urban health warnings on Devdiscourse ...

A blood sample does not have an obvious odor to a person in a lab coat. But to an electronic nose, it can carry a chemical signature that points toward disease. In a new study from Linköping ...

Abstract: Inner speech recognition has gained enormous interest in recent years due to its applications in rehabilitation, developing assistive technology, and cognitive assessment. However, since ...

WASHINGTON – The U.S. Army has established a new career pathway for officers to specialize in artificial intelligence and machine learning (AI/ML), formally designating the 49B AI/ML Officer as an ...

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...