Tech Xplore

A new method to steer AI output uncovers vulnerabilities and potential improvements

A team of researchers has found a way to steer the output of large language models by manipulating specific concepts inside ...
Tech Xplore

Study finds 'dosed' nonlinearity can beat linear and fully nonlinear AI

Umbrella or sun cap? Buy or sell stocks? When it comes to questions like these, many people today rely on AI-supported recommendations. Chatbots such as ChatGPT, AI-driven weather forecasts, and ...

Machine learning helps solve a central problem of quantum chemistry

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...
TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...

Machine-learned biomarker identifies those at high risk for liver cancer

Researchers led by Xian-Yang Qin at the RIKEN Center for Integrative Medical Sciences (IMS) in Japan have developed a score that predicts the risk of liver cancer. Published in the journal Proceedings ...
Scientific Research Publishing

Accuracy and Response Speed of Eye Center Annotation Using Eye Movement Models: Validating the Effectiveness of Eyesight Detection ()

Optokinetic Nystagmus (OKN) is a natural reflexive eye movement in oculomotor studies, reflecting the health status of the visual system. Through accurate eye center annotation, physicians can observe ...
Scientific Research Publishing

Larose, D.T. and Larose, C.D. (2014) k-Nearest Neighbor Algorithm.

ABSTRACT: This paper proposes a structured data prediction method based on Large Language Models with In-Context Learning (LLM-ICL). The method designs sample selection strategies to choose samples ...
EurekAlert!

Transforming acute exacerbations of chronic obstructivepulmonary disease (AECOPD) risk assessment: Amulti-algorithm machine learning approach for preciseclinical phenotyping

The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...
Medscape

Machine Learning Algorithm Predicts Gout Flares Using RNA

A machine learning algorithm used gene expression profiles of patients with gout to predict flares. The PyTorch neural network performed best, with an area under the curve of 65%. The PyTorch model ...
Frontiers

Machine learning-based algorithms for the prediction of 90-day survival in patients with liver failure receiving artificial liver therapy

Background: Liver failure is associated with high short-term mortality, and the predictive value of clinical factors for patients undergoing artificial liver therapy is uncertain. We aim to develop ...
National Academies of Sciences%2c Engineering%2c and Medicine

Making Machine Learning Safer in High-Stakes Settings

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...