AIMC Topic: Humans

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When AI models take the exam: large language models vs medical students on multiple-choice course exams.

Medical education online
Large language models (LLMs) are increasingly used in healthcare and medical education, but their performance on institution-authored multiple-choice questions (MCQs), particularly with negative marking, remains unclear. To compare the examination pe...

Development of explainable machine learning models to predict side effects in patients with rheumatoid arthritis taking methotrexate treatment: a nationwide multicentre cohort study.

BMJ open
OBJECTIVES: Methotrexate (MTX) effectively controls rheumatoid arthritis (RA) but often leads to side effects (SE) such as gastrointestinal (GI) issues, liver toxicity and bone marrow suppression. To develop clinically interpretable machine learning ...

Lightweight Hybrid Deep Learning Models for Accurate Classification of Respiratory Conditions from Raw Lung Sounds.

Journal of medical systems
In recent years, progress in artificial intelligence, particularly in the realm of deep learning, has resulted in substantial enhancements in the diagnosis of various medical conditions. This study introduces a framework that leverages multiple light...

Evaluation of AI models for radiology exam preparation: DeepSeek vs. ChatGPT-3.5.

Medical education online
The rapid advancement of artificial intelligence (AI) chatbots has generated significant interest regarding their potential applications within medical education. This study sought to assess the performance of the open-source large language model Dee...

DyeSPY: Establishing the First Forensic SERS Reference for Hair Dye Colorant Evidence.

Analytical chemistry
Hair dyeing is a widespread practice with potential forensic value in individual identification, yet most analytical approaches are destructive, time-intensive, or lack sensitivity for trace residues. Surface-enhanced Raman spectroscopy (SERS) offers...

Exploring the impact of endocrine-disrupting chemicals on erectile dysfunction through network toxicology and machine learning.

BMC pharmacology & toxicology
BACKGROUND: Erectile dysfunction (ED) is a common male sexual disorder with a multifactorial etiology. The exposure to endocrine-disrupting chemicals (EDCs) has been increasingly linked to reproductive health disorders in both men and women. EDCs can...

Feigning spectrum behaviour on the Neck Disability Index and Impact of Events Scale in whiplash associated disorder after motor vehicle crashes: a systematic assessment of classification models.

BMC psychology
PURPOSE: The aim of this study was to develop indices of feigning spectrum behaviour (FSB) on the Visual Analogue Pain Scale (VAS) Neck Disability Index (NDI) and Impact of Events Scale (IES) in people with whiplash associated disorder (WAD) after mo...

A deep learning framework for automated dental segmentation and diagnostic report generation from cone-beam computed tomography.

Head & face medicine
BACKGROUND: To develop a deep learning-based model that is capable of automatically segmenting teeth in cone-beam computed tomography (CBCT) images and generating auxiliary diagnostic reports.

Interpretable machine learning model based on multimodal ultrasound for bedside diagnosis of acute exacerbations in COPD.

Respiratory research
BACKGROUND: Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are associated with accelerated lung function decline and increased mortality. However, early and accurate diagnosis remains clinically challenging due to nonspecific s...

Diagnostic competence of senior dental students in detecting caries on panoramic radiographs with and without artificial intelligence assistance: a cross-sectional studycaries detection on panoramic radiographs.

BMC medical education
PURPOSE: Accurate detection of proximal dental caries on panoramic radiographs is essential for effective treatment planning and preventive care. While senior dental students gradually develop interpretative competence during their training, artifici...