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Evaluating Generative Artificial Intelligence Models' Responses to Questions About Scaphoid Fracture and Scaphoid Nonunion.

PURPOSE: To evaluate and compare the responses of ChatGPT and Google Gemini to common patient questions about scaphoid fracture and scaphoid … ty was not a key strength for either platform, highlighting a key area for improvement for AI-based large language models in clinical application. TYPE OF STUDY/LEVEL OF EVIDENCE: Diagnostic V.

Стриато-лимбическая и лобная дисфункция, лежащая в основе дисбаланса в мотивации вознаграждения и когнитивном контроле в навязанном сексуальном поведении: нейроимационный метаанализ.

СТРУКТУРА: Навязчивое сексуальное расстройство (CSBD) связано с неконтролируемыми сексуальными желаниями и поведением, вызывающими расстройство или функциональные расстройства. Несмотря на то, что он классифицируется как расстройство контроля импульсов в МКБ-11, его нейробиологическая основа и когнитивные недостатки по-прежнему плохо понимаются. Достижения в крупных языковых моделях (МЛМ) позволяют производить масштабируемую обработку литературы и синтез мультимодальных нейроимаций. В этом исследовании использовались основанные на LLM рамки для метаанализа на основе координат и функционального

Совпадение в аннотации оригинала
BACKGROUND: Compulsive sexual behavior disorder (CSBD) involves uncontrollable sexual urges and behaviors that cause distress or functional impairment. Although classified as an impulse control disorder in ICD-11, its neurobiological basis and cognitive deficits remain poorly understood. Advances in large language models (LLMs) enable scalable literature par…

Diagnostic accuracy and repeatability of ChatGPT using textual and radiographic data in reversible pulpitis: a retrospective diagnostic study.

OBJECTIVES: Large language models have recently evolved into multimodal systems capable of interpreting images alongside text. The aim of this study was to assess the diagnostic accuracy and repeatability of ChatGPT-5 for reversible pulpitis, based on structured clinical information and periapical radiographs (PRs). METHODS: Thirty expert-validated cases of reversible pulpitis were retrospectively selected. For each case, clinical data and PRs were compiled to create a reference dataset, with expert consensus serving as the reference standard. A structured prompt incorporating clinical inform…

Perceptions and Earliest Experiences of Medical Students and Faculty With ChatGPT in Medical Education: Qualitative Study.

BACKGROUND: With the rapid development of artificial intelligence technologies, there is a growing interest in the potential use of artifici … e perceptions and experiences of medical faculty and students regarding the use of newly introduced large language models like ChatGPT in medical education. While the benefits of ChatGPT were recognized, participants also expressed concerns and limitations requiring further studies for effective integration into medical education, exploring the impact of ChatGPT on lea …

Parameter-efficient fine-tuning for low-resource text classification: a comparative study of LoRA, IA3, and ReFT.

The successful application of large-scale transformer models in Natural Language Processing (NLP) is often hindered by the substantial computational cost and data requirements of full fine-tuning. This challenge is particularly acute in low-resource settings, where standard fine-tuning can lead to catastrophic overfitting and model collapse. To address this, Parameter-Efficient Fine-Tuning (PEFT) methods have emerged as a promising solution. However, a direct comparative analysis of their trade-offs under unified low-resource conditions is lacking. This study provides a rigorous empirical eval

Evaluating ChatGPT's performance across radiology subspecialties: A meta-analysis of board-style examination accuracy and variability.

INTRODUCTION: Large language models (LLMs) like ChatGPT are increasingly used in medicine due to their ability to synthesize information and support clinical decision-making. While prior research has evaluated ChatGPT's performance on medical board exams, limited data exist on radiology-specific exams especially considering prompt strategies and input modalities. This meta-analysis reviews ChatGPT's performance on radiology board-style questions, assessing accuracy across radiology subspecialties, prompt engineering methods, GPT model versions, and input modalities. METHODS: Searches in PubMe…

Cognitive profiles among dementia-free older adults and their associations with neuroimaging markers.

Prior studies have demonstrated the existence of cognitively-defined subgroups among dementia free older adults, however, it is unclear whether such subgroups are characterized by distinct neuroimaging measures of brain function and structure. To address this gap, the current study used latent profile analysis (LPA) to identify cognitively-defined subgroups in a sample of 167 (mean age = 69 years) dementia-free older adults with cognitive testing, amyloid PET, and multimodal brain MRI scans. The cognitive test scores covered the domains of episodic memory, executive function, language, and vis

The Need to Improve the Medical Subject Headings (MeSH) and the Excerpta Medica Tree (EMTREE) Thesauri to Perform Systematic Review on Oral Potentially Malignant Disorders.

BACKGROUND: Despite recent advancements in the understanding and classification of oral potentially malignant disorders (OPMD), their termin … both PubMed and Embase for OPMD studies. Moreover, the use of Embase's PubMed query translator and Large Language Models, such as ChatGPT, may lead to retrieval biases due to indexing discrepancies, posing challenges for early-career researchers and students. We recommend introducing "oral potentially malignant disorders" as a standardised subject heading. Evidence-ba …

Citizen science in dentistry and community oral health: A scoping review.

BACKGROUND: The authors aimed to identify, describe, and discuss models and experiences of citizen science in dentistry and community oral health, with a focus on moderate through large involvement of citizens in the research process. TYPES OF STUDIES REVIEWED: A search strategy was used in 6 databases and supplemented in gray literature with no restrictions on language or date. Eligible sources of evidence were observational studies, intervention studies, implementation studies, case study reports, and citizen science documents. Publications were assessed for final inclusion according to the

Artificial intelligence in blood donor management: A narrative review.

Blood transfusions are vital in health care, yet maintaining an adequate and safe blood supply remains a significant challenge. To address blood donation-associated challenges, this review explores how integrating artificial intelligence (AI) technologies can improve donor recruitment, retention and management. For instance, robotic process automation can streamline repetitive administrative tasks, allowing staff to focus on more critical activities and improving efficiency. When augmented with AI techniques such as machine learning (ML) and natural language processing, it transitions from sta

Understanding bullying as a significant predictor of posttraumatic stress symptoms in adolescents: insights from clinical samples in Norway, The Netherlands and Germany.

BACKGROUND: Research on bullying and child PTSD has traditionally been conducted separately. This study examines the association between bullying and posttraumatic stress symptoms (PTSS) in three international samples, comparing its impact to other potentially traumatic events (PTEs) and assessing whether bullying predicts PTSS when controlling for other PTEs. METHOD: We analyzed three large clinical samples of children and adolescents referred for mental health care in Norway (N = 3370, 63.4% female, Mage = 14.0), the Netherlands (N = 952, 68.7% female, Mage = 15.57), and Germany (N = 707, 3

Artificial Intelligence-Based Virtual Assistant for the Diagnostic Approach of Chronic Ataxias.

BACKGROUND: Chronic ataxias, a complex group of over 300 diseases, pose significant diagnostic challenges because of their clinical and genetic heterogeneity. Here, we propose that artificial intelligence (AI) can aid in the identification and understanding of these disorders through the utilization of a smart virtual assistant. OBJECTIVES: The aim is to develop and validate an AI-powered virtual assistant for diagnosing chronic ataxias. METHODS: A non-commercial virtual assistant was developed using advanced algorithms, decision trees, and large language models. In the validation process, 4…

Detectable AI-Generated Text in the Journal of Craniofacial Surgery : A Comparison of 2014 and 2024 Publications.

BACKGROUND: The rapid emergence of large language models (LLMs) has transformed scientific writing, prompting concerns regarding the extent to which generative artificial intelligence (AI) tools may be influencing published research manuscripts. AI-detection software has been proposed as a method to identify AI-generated text; however, the validity of these tools in scientific contexts remains uncertain. This study evaluates detectable AI content in articles published in the Journal of Craniofacial Surgery (JCFS) before and after the widespread adoption of LLMs. METHODS: A retrospective cross…

Prevention of bicalutamide-induced breast events in patients with prostate cancer: a meta-analysis of randomized controlled trials.

PURPOSE: This study aimed to quantitatively assess the effectiveness of tamoxifen, anastrozole, and radiotherapy in preventing bicalutamide-induced breast events-specifically gynecomastia and breast pain-in patients with prostate cancer. METHODS: A systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted according to PRISMA-P guidelines. A comprehensive search was performed in PubMed, Scopus, and Web of Science for English-language studies without temporal restrictions. Studies were included if they involved prostate cancer patients treated with bicalutamide re

Textural analysis as an instrument to detect differences on sacral chordoma MRI post-radiation therapy.

OBJECTIVE: Sacral chordoma is a rare bone tumor frequently treated with pre-surgical radiation; however, treatment response is difficult to … tracted, analyzed, and classified. Secondly, all the coronal T1-weighted images were compared using large language models (LLM) to extract texture features. RESULTS: A total of 22 patients received pre-surgical radiation therapy (RT) and obtained pre- and post-radiation therapy MRI. A linear discriminant analysis model of the top 10 texture analysis features classifie …

AI-based modality-agnostic classification system for vascular calcifications.

The importance of vascular calcification in major adverse cardiovascular events such as heart attacks or strokes has been established. However, calcifications have heterogeneous phenotypes, and their influence on diseased tissue stability remains poorly understood. Precise classification of calcification phenotypes is therefore essential for determining their impact on tissue stability through clinical and basic science studies. Here, we introduce a new classification system for phenotyping calcification along with a semi-automatic, non-destructive pipeline that can distinguish these phenotype

Artificial Intelligence in Oculoplastics: A Review.

PURPOSE: Innovations in artificial intelligence (AI) have paved the way for automated analysis and detection of various anterior and posteri … rteritis, lacrimal gland or lacrimal duct, dacryoadenitis, orbital fracture, orbital infections. AI large language models were excluded. RESULTS: This review included 19 studies on eyelid and brow ptosis, 16 on periocular and intraocular cancer, 9 on orbital trauma and tumors, 17 on autoimmune, infectious, and inflammatory conditions of the orbit and malformations, an …

Evaluation of the Reliability of ChatGPT to Provide Guidance on Recombinant Zoster Vaccination for Patients With Rheumatic and Musculoskeletal Diseases.

INTRODUCTION: Large language models (LLMs) such as ChatGPT can potentially transform the delivery of health information. This study aims to evaluate the accuracy and completeness of ChatGPT in responding to questions on recombinant zoster vaccination (RZV) in patients with rheumatic and musculoskeletal diseases. METHODS: A cross-sectional study was conducted using 20 prompts based on information from the Centers for Disease Control and Prevention (CDC), the Advisory Committee on Immunization Practices (ACIP), and the American College of Rheumatology (ACR). These prompts were inputted into Cha…

NLP-driven analysis of electronic health records for early Identification of tuberculosis cases.

Tuberculosis (TB) is still one of the biggest health problems in the world. Each year, millions of people get it, and because diagnosis are often delayed, the disease spreads and kills more people. Radiographic examination and sputum smear microscopy are two common ways to find TB, but they aren't very sensitive, need skilled staff, and can't be used on a large scale in places with few resources. Because of this, adding Natural Language Processing (NLP) to Electronic Health Records (EHRs) has become a promising way to find TB more quickly. This study proposes an NLP-driven framework that lever

GPT-4 Performance for Neurologic Localization.

BACKGROUND AND OBJECTIVES: In health care, large language models such as Generative Pretrained Transformers (GPTs), trained on extensive text datasets, have potential applications in reducing health care disparities across regions and populations. Previous software developed for lesion localization has been limited in scope. This study aims to evaluate the capability of GPT-4 for lesion localization based on clinical presentation. METHODS: GPT-4 was prompted using history and neurologic physical examination (H&P) from published cases of acute stroke followed by questions for clinical reasonin…