ChatGPT and other artificial intelligence (AI) tools can modify nutritional management in clinical settings. These technologies, based on machine learning and deep learning, enable the identification of risks, the proposal of personalized interventio...
Studies in health technology and informatics
Sep 3, 2025
INTRODUCTION: The quality and reproducibility of research results from biological samples are significantly influenced by the pre-analytical variability resulting from different conditions during sample collection, storage and processing. Although nu...
The journal of applied laboratory medicine
Sep 3, 2025
BACKGROUND: Artificial intelligence (AI) models are increasingly used in academic and clinical settings that require information synthesis and decision-making. This study explores the performance, accuracy, and reproducibility of 3 OpenAI models-GPT-...
BACKGROUND: Diagnosis of soil-transmitted helminthiasis and schistosomiasis for surveillance relies on microscopic detection of ova in Kato-Katz (KK) prepared slides. Artificial intelligence (AI)-based platforms for parasitic eggs may be developed us...
Large multimodal models, a type of generative artificial intelligence (AI), could contribute to wider government efforts to achieve universal health coverage if ethical challenges are proactively addressed during the design and deployment of these AI...
Antimicrobial resistance (AMR) remains a critical global health threat, with significant impacts on individuals and healthcare systems, particularly in low-income countries. By 2019, AMR was responsible for >4.9 million fatalities globally, and proje...
In critical care medicine, sepsis management represents a critical barrier to improving clinical outcomes, primarily due to the disease's profound heterogeneity and the current inability to optimally identify patient subgroups benefiting from persona...
The risk of acute respiratory distress syndrome (ARDS) combined with acute kidney injury (AKI) is high and the prognosis is poor. Therefore, there is an urgent need for efficient and accurate methods to improve clinical doctors' early diagnosis and p...
Artificial intelligence (AI) in breast imaging has garnered significant attention given the numerous reports of improved efficiency, accuracy, and the potential to bridge the gap of expanded volume in the face of limited physician resources. While AI...
Artificial intelligence (AI) and machine learning (ML), used injudiciously, have the potential to exacerbate health inequalities. Conversely, there is a potential to use ML to give insight into the impact of socioeconomic factors, which allows us to ...
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