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An Ultra-Brief Informant Questionnaire for Case Finding of Cognitive Impairment Across Diverse Literacy: Diagnostic Accuracy Study.

JMIR aging
BACKGROUND: Undiagnosed cognitive impairment poses a global challenge, prompting recent interest in ultra-brief screening questionnaires (comprising <2 to 3 items) to efficiently identify individuals needing further evaluation. However, evidence on u...

AI Literacy Among Chinese Medical Students: Cross-Sectional Examination of Individual and Environmental Factors.

JMIR medical education
BACKGROUND: Artificial intelligence (AI) literacy is increasingly essential for medical students. However, without systematic characterization of the relevant components, designing targeted medical education interventions may be challenging.

Comparing AI-Assisted Problem-Solving Ability With Internet Search Engine and e-Books in Medical Students With Variable Prior Subject Knowledge: Cross-Sectional Study.

JMIR medical education
BACKGROUND: Artificial intelligence (AI), particularly large language models (LLMs) such as ChatGPT (OpenAI), is rapidly influencing medical education. Its effectiveness for students with varying levels of prior knowledge remains underexplored.

PRIME: an interpretable artificial intelligence model based on liquid biopsy improves prediction of progression risk in non-small cell lung cancer.

Military Medical Research
BACKGROUND: Despite the predictive impact of circulating tumor DNA (ctDNA) minimal residual disease (MRD), accurate prediction of failure risk after curative-intent treatments for early-stage or localized non-small cell lung cancer (NSCLC) patients t...

Integrative multi-omics and network-based machine learning for early diagnosis of Parkinson's disease.

PloS one
BACKGROUND: Accurate diagnosis of Parkinson's Disease (PD) remains challenging due to its biological complexity. Integrating machine learning with multi-omics and network topological analyses may enhance diagnostic precision.

Representativeness of a German AI-enabled data network for secondary epidemiological analysis based on electronic health records.

PloS one
INTRODUCTION: The ongoing digitalization of medicine, increased computing power and low-cost storage capacities enable the use of AI-based algorithms for epidemiological big data analysis of electronic patient records. The aim of this study was to ev...

Machine learning for screening laryngopharyngeal reflux symptoms in college students: a cross-sectional study.

Annals of medicine
BCKGROUND: Laryngopharyngeal reflux (LPR) is a widespread global health issue. Its recurring symptoms and impact on quality of life create significant economic burdens for individuals and society. To examine the links between lifestyle, diet, and LPR...

Mapping dental biofilms: from plaque index through planimetry to volumetric analysis.

Clinical oral investigations
OBJECTIVES: Conventional plaque assessment methods, such as clinical indices and planimetry, rely on plaque-disclosing agents and may overemphasize thin biofilm areas due to plaque thickness variations. This study introduces a digital 3D method to qu...

Development of liquid biopsy for screening colorectal cancer through the combination of an antibody microarray-based metal-enhanced sandwich immunofluorescent assay of cytokines with machine learning.

The Analyst
The simultaneous determination of the expression levels of multiple inflammation-associated cytokines in blood holds great promise for the early screening of cancer including colorectal cancer (CRC). Herein, an antibody microarray-based sandwich meta...

Evaluating AI chatbots in neurological function test interpretation for brain tumor surgery.

Neurosurgical review
Neuropsychological assessments are essential for evaluating functional status and guiding surgical planning in patients with brain tumors. However, their complexity may hinder interpretation for patients and junior clinicians. Large language model (L...