AIMC Topic: Humans

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Artificial Intelligence Models for Pediatric Lung Sound Analysis: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: Pediatric respiratory diseases, including asthma and pneumonia, are major causes of morbidity and mortality in children. Auscultation of lung sounds is a key diagnostic tool but is prone to subjective variability. The integration of artif...

Diagnosis Test Accuracy of Artificial Intelligence for Endometrial Cancer: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: Endometrial cancer is one of the most common gynecological tumors, and early screening and diagnosis are crucial for its treatment. Research on the application of artificial intelligence (AI) in the diagnosis of endometrial cancer is incr...

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...

Decoding Recurrence in Early-Stage and Locoregionally Advanced Non-Small Cell Lung Cancer: Insights From Electronic Health Records and Natural Language Processing.

JCO clinical cancer informatics
PURPOSE: Recurrences after curative resection in early-stage and locoregionally advanced non-small cell lung cancer (NSCLC) are common, necessitating a nuanced understanding of associated risk factors. This study aimed to establish a natural language...

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...

Convolutional Neural Network approach to classify mitochondrial morphologies.

Computational biology and chemistry
The morphology of the mitochondrial network is a major indicator of cellular health and function, with changes often linked to various physiological and pathological conditions. As a result, efficient methods to quickly assess mitochondrial shape in ...

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...