AIMC Topic: Reproducibility of Results

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The Role of Artificial Intelligence Large Language Models in Literature Search Assistance to Evaluate Inguinal Hernia Repair Approaches.

Journal of laparoendoscopic & advanced surgical techniques. Part A
This study assesses the reliability of artificial intelligence (AI) large language models (LLMs) in identifying relevant literature comparing inguinal hernia repair techniques. We used LLM chatbots (Bing Chat AI, ChatGPT versions 3.5 and 4.0, and G...

AI-supported approaches for mammography single and double reading: A controlled multireader study.

European journal of radiology
PURPOSE: To assess the impact of artificial intelligence (AI) on the diagnostic performance of radiologists with varying experience levels in mammography reading, considering single and simulated double reading approaches.

Deep learning-driven multi-class classification of brain strokes using computed tomography: A step towards enhanced diagnostic precision.

European journal of radiology
OBJECTIVE: To develop and validate deep learning models leveraging CT imaging for the prediction and classification of brain stroke conditions, with the potential to enhance accuracy and support clinical decision-making.

Keeping AI on Track: Regular monitoring of algorithmic updates in mammography.

European journal of radiology
PURPOSE: To demonstrate a method of benchmarking the performance of two consecutive software releases of the same commercial artificial intelligence (AI) product to trained human readers using the Personal Performance in Mammographic Screening scheme...

Whole Brain 3D T1 Mapping in Multiple Sclerosis Using Standard Clinical Images Compared to MP2RAGE and MR Fingerprinting.

NMR in biomedicine
Quantitative T1 and T2 mapping is a useful tool to assess properties of healthy and diseased tissues. However, clinical diagnostic imaging remains dominated by relaxation-weighted imaging without direct collection of relaxation maps. Dedicated resear...

AI in clinical decision-making: ChatGPT-4 vs. Llama2 for otolaryngology cases.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: To evaluate the diagnostic accuracy, appropriateness of additional examination recommendations, and consistency of therapeutic regimens by ChatGPT-4 and Llama2 based on real otolaryngology cases.

Comparative analysis of GPT-4 and Google Gemini's consistency with pediatric otolaryngology guidelines.

International journal of pediatric otorhinolaryngology
OBJECTIVE: To evaluate the accuracy and completeness of large language models (LLMs) in interpreting pediatric otolaryngology guidelines.

Comparative Performance of Anthropic Claude and OpenAI GPT Models in Basic Radiological Imaging Tasks.

Journal of medical imaging and radiation oncology
BACKGROUND: Publicly available artificial intelligence (AI) Vision Language Models (VLMs) are constantly improving. The advent of vision capabilities on these models could enhance radiology workflows. Evaluating their performance in radiological imag...

Machine learning-based prediction of hearing loss: Findings of the US NHANES from 2003 to 2018.

Hearing research
The prevalence of hearing loss (HL) has emerged as an escalating public health concern globally. The objective of this study was to leverage data from the National Health and Nutritional Examination Survey (NHANES) to develop an interpretable predict...