Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries? Theoretical ...

The severity of symptoms in posttraumatic stress disorder (PTSD) varies greatly across individuals in the first year after trauma and it remains difficult to predict whether someone might worsen, ...

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

Recent advances in machine learning have opened transformative avenues for investigating complex problems in string theory and geometry. By integrating sophisticated algorithms with theoretical ...

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

MIT researchers have developed a technique to identify and remove specific data points in training datasets that disproportionately contribute to a model's errors on minority subgroups. This approach ...

ML tailors banking solutions by analyzing transactions, spending habits, and financial goals. It detects fraud in real time, adapts to threats, and verifies customer identity behaviorally. AI chatbots ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...