AIMC Topic: Adult

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Lipidomic analysis coupled with machine learning identifies unique urinary lipid signatures in patients with interstitial cystitis/bladder pain syndrome.

World journal of urology
PURPOSE: To identify biomarkers for diagnosis and classification of interstitial cystitis/bladder pain syndrome (IC/BPS) by urinary lipidomics coupled with machine learning.

Effect of Uncertainty-Aware AI Models on Pharmacists' Reaction Time and Decision-Making in a Web-Based Mock Medication Verification Task: Randomized Controlled Trial.

JMIR medical informatics
BACKGROUND: Artificial intelligence (AI)-based clinical decision support systems are increasingly used in health care. Uncertainty-aware AI presents the model's confidence in its decision alongside its prediction, whereas black-box AI only provides a...

Stigmatisation of gambling disorder in social media: a tailored deep learning approach for YouTube comments.

Harm reduction journal
BACKGROUND: The stigmatisation of gamblers, particularly those with a gambling disorder, and self-stigmatisation are considered substantial barriers to seeking help and treatment. To develop effective strategies to reduce the stigma associated with g...

Daily Automated Prediction of Delirium Risk in Hospitalized Patients: Model Development and Validation.

JMIR medical informatics
BACKGROUND: Delirium is common in hospitalized patients and is correlated with increased morbidity and mortality. Despite this, delirium is underdiagnosed, and many institutions do not have sufficient resources to consistently apply effective screeni...

DWI of the rectum with deep learning reconstruction: comparison of PROPELLER, reduced FOV, and conventional DWI.

Abdominal radiology (New York)
PURPOSE: To compare the image quality and diagnostic performance of periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER), reduced field-of-view (rFOV), and conventional diffusion-weighted imaging (cDWI) combined wi...

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...

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...

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).