AIMC Topic: Reproducibility of Results

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[Rare disease in the age of artificial intelligence.].

Recenti progressi in medicina
INTRODUCTION: The text examines the impact of artificial intelligence (AI) in the context of rare diseases, exploring how patients turn to AI resources for health information, especially in situations where doctor-patient communication is limited. Th...

Application of Artificial Intelligence in Infant Movement Classification: A Reliability and Validity Study in Infants Who Were Full-Term and Preterm.

Physical therapy
OBJECTIVE: Preterm infants are at high risk of neuromotor disorders. Recent advances in digital technology and machine learning algorithms have enabled the tracking and recognition of anatomical key points of the human body. It remains unclear whethe...

Development of a pharmaceutical science systematic review process using a semi-automated machine learning tool: Intravenous drug compatibility in the neonatal intensive careĀ setting.

Pharmacology research & perspectives
Our objective was to establish and test a machine learning-based screening process that would be applicable to systematic reviews in pharmaceutical sciences. We used the SPIDER (Sample, Phenomenon of Interest, Design, Evaluation, Research type) model...

Skeletal facial asymmetry: reliability of manual and artificial intelligence-driven analysis.

Dento maxillo facial radiology
OBJECTIVES: To compare artificial intelligence (AI)-driven web-based platform and manual measurements for analysing facial asymmetry in craniofacial CT examinations.

DOME Registry: implementing community-wide recommendations for reporting supervised machine learning in biology.

GigaScience
Supervised machine learning (ML) is used extensively in biology and deserves closer scrutiny. The Data Optimization Model Evaluation (DOME) recommendations aim to enhance the validation and reproducibility of ML research by establishing standards for...

Benchmarking the most popular XAI used for explaining clinical predictive models: Untrustworthy but could be useful.

Health informatics journal
OBJECTIVE: This study aimed to assess the practicality and trustworthiness of explainable artificial intelligence (XAI) methods used for explaining clinical predictive models.

From open-ended to multiple-choice: evaluating diagnostic performance and consistency of ChatGPT, Google Gemini and Claude AI.

Wiadomosci lekarskie (Warsaw, Poland : 1960)
OBJECTIVE: Aim: To determine the performance and response repeatability of freely available LLMs in diagnosing diseases based on clinical case descriptions.

Enhancing coronary artery plaque analysis via artificial intelligence-driven cardiovascular computed tomography.

Therapeutic advances in cardiovascular disease
Coronary computed tomography angiography (CCTA) is a noninvasive imaging modality of cardiac structures and vasculature considered comparable to invasive coronary angiography for the evaluation of coronary artery disease (CAD) in several major cardio...

Evaluation of the reliability and readability of answers given by chatbots to frequently asked questions about endophthalmitis: A cross-sectional study on chatbots.

Health informatics journal
This study aimed to investigate the accuracy, reliability, and readability of A-Eye Consult, ChatGPT-4.0, Google Gemini and Copilot AI large language models (LLMs) in responding to patient questions about endophthalmitis. The LLMs' responses to 25 ...

Performance and Reliability Evaluation of an Automated Bone-Conduction Audiometry Using Machine Learning.

Trends in hearing
To date, pure-tone audiometry remains the gold standard for clinical auditory testing. However, pure-tone audiometry is time-consuming and only provides a discrete estimate of hearing acuity. Here, we aim to address these two main drawbacks by develo...