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Probiotic Supplements Benefit Psoriasis Therapy Rather Than Affecting Disease Risk: Evidence from NHANES Machine-Learning and Meta-Analysis Study.

Probiotics and antimicrobial proteins
This research aimed to evaluate the impact of probiotic supplementation on the severity of psoriasis symptoms and its association with the risk of developing the disease. We analyzed the association between probiotic usage and psoriasis among 21,942 ...

Prediction of Nursing Need Proxies Using Vital Signs and Biomarkers Data: Application of Deep Learning Models.

Journal of clinical nursing
AIM: To develop deep learning models to predict nursing need proxies among hospitalised patients and compare their predictive efficacy to that of a traditional regression model.

Translating ophthalmic medical jargon with artificial intelligence: a comparative comprehension study.

Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
OBJECTIVE: Our goal was to evaluate the efficacy of OpenAI's ChatGPT-4.0 large language model (LLM) in translating technical ophthalmology terminology into more comprehensible language for allied health care professionals and compare it with other LL...

Predicting Early Hospital Discharge Following Revision Total Hip Arthroplasty: An Analysis of a Large National Database Using Machine Learning.

The Journal of arthroplasty
BACKGROUND: Revision total hip arthroplasty (rTHA) was recently removed from the Medicare inpatient-only list. However, appropriate candidate selection for outpatient rTHA remains paramount. The purpose of this study was to evaluate the utility of a ...

Development and application of an intelligent pressure injury assessment system using AI image recognition.

Technology and health care : official journal of the European Society for Engineering and Medicine
BackgroundPressure injuries are a significant concern in clinical settings, requiring accurate assessment to prevent complications. Traditional assessment methods are often subjective and time-consuming.ObjectiveThis study aimed to develop and evalua...

Breast cancer detection and classification with digital breast tomosynthesis: a two-stage deep learning approach.

Diagnostic and interventional radiology (Ankara, Turkey)
PURPOSE: The purpose of this study was to propose a new computer-assisted two-staged diagnosis system that combines a modified deep learning (DL) architecture (VGG19) for the classification of digital breast tomosynthesis (DBT) images with the detect...

Utility of a Large Language Model for Extraction of Clinical Findings from Healthcare Data following Lung Ablation: A Feasibility Study.

Journal of vascular and interventional radiology : JVIR
To assess the feasibility of utilizing a large language model (LLM) in extracting clinically relevant information from healthcare data in patients who have undergone microwave ablation for lung tumors. In this single-center retrospective study, radio...

Predicting 30-day reoperation following primary total knee arthroplasty: machine learning model outperforms the ACS risk calculator.

Medical & biological engineering & computing
The ACS risk calculator (ARC) has proven less effective in predicting patient-specific risk of early reoperation after primary total knee arthroplasty (TKA), compromising care quality and cost efficiency. This study compared the performance of a mach...