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Cross-Sectional Studies
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Natural Language Processing to Identify Infants Aged 90 Days and Younger With Fevers Prior to Presentation.
Hospital pediatrics
Jan 1, 2025
OBJECTIVE: Natural language processing (NLP) can enhance research studies for febrile infants by more comprehensive cohort identification. We aimed to refine and validate an NLP algorithm to identify and extract quantified temperature measurements fr...
Deconstructing Cognitive Impairment in Psychosis With a Machine Learning Approach.
JAMA psychiatry
Jan 1, 2025
IMPORTANCE: Cognitive functioning is associated with various factors, such as age, sex, education, and childhood adversity, and is impaired in people with psychosis. In addition to specific effects of the disorder, cognitive impairments may reflect a...
[Artificial intelligence model for diagnosis of coronary artery disease based on facial photos].
Zhonghua xin xue guan bing za zhi
Nov 24, 2024
To develop and validate an artificial intelligence (AI) diagnostic model for coronary artery disease based on facial photos. This study was a cross-sectional study. Patients who were scheduled to undergo coronary angiography (CAG) at Beijing Anzhen...
Influence of vitamin D and calcium-sensing receptor gene variants on calcium metabolism in end-stage renal disease: insights from machine learning analysis.
European review for medical and pharmacological sciences
Nov 1, 2024
OBJECTIVE: End-stage renal disease (ESRD) commonly manifests with disrupted calcium balance, leading to renal osteodystrophy. We posited that variations in the genetic makeup of vitamin D and calcium-sensing receptors, specifically single nucleotide ...
Physician Opinions on Artificial Intelligence Chatbots In Dermatology: A National Online Cross-Sectional Survey of Dermatologists.
Journal of drugs in dermatology : JDD
Nov 1, 2024
BACKGROUND: Artificial intelligence chatbots (AIC) have sharply risen in popularity. Dermatology, heavily involving visual, clinical, and pathological pattern-recognition techniques, will be impacted by AIC. Thus, this study aims to categorize the at...
Machine learning prediction of early recurrence after surgery for gallbladder cancer.
The British journal of surgery
Oct 30, 2024
BACKGROUND: Gallbladder cancer is often associated with poor prognosis, especially when patients experience early recurrence after surgery. Machine learning may improve prediction accuracy by analysing complex non-linear relationships. The aim of thi...
A Meta-Learning Approach for Classifying Multimodal Retinal Images of Retinal Vein Occlusion With Limited Data.
Translational vision science & technology
Sep 3, 2024
PURPOSE: To propose and validate a meta-learning approach for detecting retinal vein occlusion (RVO) from multimodal images with only a few samples.
Artificial intelligence classifies primary progressive aphasia from connected speech.
Brain : a journal of neurology
Sep 3, 2024
Neurodegenerative dementia syndromes, such as primary progressive aphasias (PPA), have traditionally been diagnosed based, in part, on verbal and non-verbal cognitive profiles. Debate continues about whether PPA is best divided into three variants an...
Machine Learning-Assisted Analysis of Sublingual Microcirculatory Dysfunction for Early Cardiovascular Risk Evaluation and Cardiovascular-Kidney-Metabolic Syndrome Stage in Patients With Type 2 Diabetes Mellitus.
Diabetes/metabolism research and reviews
Sep 1, 2024
AIMS: To examine whether sublingual microcirculation can be used as an effective and noninvasive method for assessing cardiovascular, kidney, and metabolic risks in patients with type 2 diabetes mellitus (T2DM).
Assessment of readability, reliability, and quality of ChatGPT®, BARD®, Gemini®, Copilot®, Perplexity® responses on palliative care.
Medicine
Aug 16, 2024
There is no study that comprehensively evaluates data on the readability and quality of "palliative care" information provided by artificial intelligence (AI) chatbots ChatGPT®, Bard®, Gemini®, Copilot®, Perplexity®. Our study is an observational and...
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