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Generative AI responses are a dime a dozen; Making them count is the challenge - Evaluating information presentation styles in healthcare chatbots using hierarchical Bayesian regression models.

Applied ergonomics
The emergence of large language models offers new opportunities to deliver effective healthcare information through web-based healthcare chatbots. Health information is often complex and technical, making it crucial to design human-AI interactions th...

Machine learning based radiomic models outperform clinical biomarkers in predicting outcomes after immunotherapy for hepatocellular carcinoma.

Journal of hepatology
BACKGROUND & AIMS: Atezolizumab plus bevacizumab (A/B) is a first-line therapy for unresectable hepatocellular carcinoma (HCC). Only a small proportion of patients respond to treatment. This study integrated radiomic and clinical data derived from ro...

Exploring the potential of large language models to understand interpersonal emotion regulation strategies from narratives.

Emotion (Washington, D.C.)
Interpersonal emotion regulation involves using diverse strategies to influence others' emotions, commonly assessed with questionnaires. However, this method may be less effective for individuals with limited literacy or introspection skills. To addr...

Multi-modal multi-task deep neural networks for sleep disordered breathing assessment using cardiac and audio signals.

International journal of medical informatics
BACKGROUND AND OBJECTIVE: Sleep disordered breathing (SDB) is one of the most common sleep disorders and has short-term consequences for daytime functioning while being a risk factor for several conditions, such as cardiovascular disease. Polysomnogr...

Combined peritumoral radiomics and clinical features predict 12-month progression free survival in glioblastoma.

Journal of neuro-oncology
PURPOSE: Analyzing post-treatment MRIs from glioblastoma patients can be challenging due to similar radiological presentations of disease progression and treatment effects. Identifying radiomics features (RFs) revealing progressive glioblastoma can c...

Fully Automated Online Adaptive Radiation Therapy Decision-Making for Cervical Cancer Using Artificial Intelligence.

International journal of radiation oncology, biology, physics
BACKGROUND: Interfraction variations during radiation therapy pose a challenge for patients with cervical cancer, highlighting the benefits of online adaptive radiation therapy (oART). However, adaptation decisions rely on subjective image reviews by...

Surface-Enhanced Raman Scattering (SERS) combined with machine learning enables accurate diagnosis of cervical cancer: From molecule to cell to tissue level.

Critical reviews in oncology/hematology
The rising number of cervical cancer cases is placing a heavy economic strain on the country and its people. Improving survival rates hinges on early detection, precise diagnosis, and thorough treatment. Common screening and diagnostic methods like P...

Use of a priority lane to increase voluntary visits to a milking robot in dairy cows.

Journal of dairy science
Voluntary visits to the milking robot are the basis of automatic milking system functionality. Therefore, problems arise when cows are undermotivated to visit the robot. Cows with reduced competitive abilities, specifically those that are lame or low...

Development and Validation an AI Model to Improve the Diagnosis of Deep Infiltrating Endometriosis for Junior Sonologists.

Ultrasound in medicine & biology
OBJECTIVE: This study aims to develop and validate an artificial intelligence (AI) model based on ultrasound (US) videos and images to improve the performance of junior sonologists in detecting deep infiltrating endometriosis (DE).

Transcriptomic analyses of human brains with Alzheimer's disease identified dysregulated epilepsy-causing genes.

Epilepsy & behavior : E&B
BACKGROUND & OBJECTIVE: Alzheimer's Disease (AD) patients at multiple stages of disease progression have a high prevalence of seizures. However, whether AD and epilepsy share pathophysiological changes remains poorly defined. In this study, we levera...