AIMC Topic: Clinical Competence

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Evaluating the Effectiveness of advanced large language models in medical Knowledge: A Comparative study using Japanese national medical examination.

International journal of medical informatics
UNLABELLED: Study aims and objectives. This study aims to evaluate the accuracy of medical knowledge in the most advanced LLMs (GPT-4o, GPT-4, Gemini 1.5 Pro, and Claude 3 Opus) as of 2024. It is the first to evaluate these LLMs using a non-English m...

Deep learning prediction of error and skill in robotic prostatectomy suturing.

Surgical endoscopy
BACKGROUND: Manual objective assessment of skill and errors in minimally invasive surgery have been validated with correlation to surgical expertise and patient outcomes. However, assessment and error annotation can be subjective and are time-consumi...

Mastery Learning Guided by Artificial Intelligence Is Superior to Directed Self-Regulated Learning in Flexible Bronchoscopy Training: An RCT.

Respiration; international review of thoracic diseases
INTRODUCTION: Simulation-based training has proven effective for learning flexible bronchoscopy. However, no studies have tested the efficacy of training toward established proficiency criteria, i.e., mastery learning (ML). We wish to test the effect...

Novel multimodal sensing and machine learning strategies to classify cognitive workload in laparoscopic surgery.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: Surgeons can experience elevated cognitive workload (CWL) during surgery due to various factors including operative technicalities and the environmental demands of the operating theatre. This can result in poorer outcomes and have a detri...

A Machine Learning Model Based on Global Mammographic Radiomic Features Can Predict Which Normal Mammographic Cases Radiology Trainees Find Most Difficult.

Journal of imaging informatics in medicine
This study aims to investigate whether global mammographic radiomic features (GMRFs) can distinguish hardest- from easiest-to-interpret normal cases for radiology trainees (RTs). Data from 137 RTs were analysed, with each interpreting seven education...

Enhancing Radiologists' Performance in Detecting Cerebral Aneurysms Using a Deep Learning Model: A Multicenter Study.

Academic radiology
RATIONALE AND OBJECTIVES: This study aimed to develop a deep learning (DL)-based model for detecting and diagnosing cerebral aneurysms in clinical settings, with and without human assistance.

Development of Machine Learning Copilot to Assist Novices in Learning Flexible Laryngoscopy.

The Laryngoscope
OBJECTIVES: Here we describe the development and pilot testing of the first artificial intelligence (AI) software "copilot" to help train novices to competently perform flexible fiberoptic laryngoscopy (FFL) on a mannikin and improve their uptake of ...

Implementation of machine learning models as a quantitative evaluation tool for preclinical studies in dental education.

Journal of dental education
PURPOSE AND OBJECTIVE: Objective, valid, and reliable evaluations are needed in order to develop haptic skills in dental education. The aim of this study is to investigate the validity and reliability of the machine learning method in evaluating the ...

ChatGPT and trainee performances in the management of maxillofacial patients.

Journal of stomatology, oral and maxillofacial surgery
INTRODUCTION: ChatGPT is an artificial intelligence based large language model with the ability to generate human-like response to text input, its performance has already been the subject of several studies in different fields. The aim of this study ...

Artificial intelligence large language model scores highly on focused practice designation in metabolic and bariatric surgery board practice questions.

Surgical endoscopy
BACKGROUND: Artificial intelligence models such as ChatGPT (Open AI) have performed well on the exams of various medical and surgical fields. It is not yet known how ChatGPT performs on similar metabolic and bariatric surgery (MBS) questions.