AI Medical Compendium Topic

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Cross-Sectional Studies

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Allied Health Professionals' Perceptions of Artificial Intelligence in the Clinical Setting: Cross-Sectional Survey.

JMIR formative research
BACKGROUND: Artificial intelligence (AI) has the potential to address growing logistical and economic pressures on the health care system by reducing risk, increasing productivity, and improving patient safety; however, implementing digital health te...

Development and validation of a web-based calculator for determining the risk of psychological distress based on machine learning algorithms: A cross-sectional study of 342 lung cancer patients.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PURPOSE: Early and accurate identification of the risk of psychological distress allows for timely intervention and improved prognosis. Current methods for predicting psychological distress among lung cancer patients using readily available data are ...

Use of large language models as artificial intelligence tools in academic research and publishing among global clinical researchers.

Scientific reports
With breakthroughs in Natural Language Processing and Artificial Intelligence (AI), the usage of Large Language Models (LLMs) in academic research has increased tremendously. Models such as Generative Pre-trained Transformer (GPT) are used by researc...

Diabetes and Cataracts Development-Characteristics, Subtypes and Predictive Modeling Using Machine Learning in Romanian Patients: A Cross-Sectional Study.

Medicina (Kaunas, Lithuania)
Diabetes has become a global epidemic, contributing to significant health challenges due to its complications. Among these, diabetes can affect sight through various mechanisms, emphasizing the importance of early identification and management of vi...

A novel interpretable deep learning model for diagnosis in emergency department dyspnoea patients based on complete data from an entire health care system.

PloS one
BACKGROUND: Dyspnoea is one of the emergency department's (ED) most common and deadly chief complaints, but frequently misdiagnosed and mistreated. We aimed to design a diagnostic decision support which classifies dyspnoeic ED visits into acute heart...

Mortality Prediction in Patients With Breast Cancer by Artificial Neural Network Model and Elastic Net Regression.

Journal of research in health sciences
BACKGROUND: Breast cancer (BC) is the most common cancer in women, and it is important to identify models that can accurately predict mortality in patients with this cancer. The aim of the present study was to use the elastic net regression and artif...

Nonlinear relationship between serum Klotho and chronic kidney disease in US adults with metabolic syndrome.

Frontiers in endocrinology
BACKGROUND: Current evidence regarding the effects of serum Klotho among patients with metabolic syndrome (MetS) is scarce. This study explored the relationship between serum Klotho levels and the odds of chronic kidney disease (CKD) in middle-aged a...

Effect of wearable robot Bot Fit's hip joint-centered assist torque and voice coach on walking.

BMC musculoskeletal disorders
BACKGROUND: The main key to the 4th industrial era is robots, and wearable robots are incorporated into human healthcare. Samsung Electronics' Bot Fit is a hip joint-centered assistive robot that can induce walking posture and energetic walking exerc...

Exploring correlates of high psychiatric inpatient utilization in Switzerland: a descriptive and machine learning analysis.

BMC psychiatry
BACKGROUND: This study investigated socio-demographic, psychiatric, and psychological characteristics of patients with high versus low utilization of psychiatric inpatient services. Our objective was to better understand the utilization pattern and t...