Artificial Intelligence Medical Compendium

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BACKGROUND: The aim of this study was to construct a machine learning (ML) model to predict the effect of dietary antioxidants on cardiovascular-arthritis comorbidity. METHODS: In this study, 44 dietary antioxidants were selected based on the Nationa... read more 

This perspective highlights the evolution of techniques for automating the synthesis of colloidal nanocrystals. Over the past 25 years, microfluidic reactors and robotic workflows have been developed to enhance the reproducibility of nanocrystal synt... read more 

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As generative artificial intelligence (AI) systems such as ChatGPT become increasingly popular sources of health information, understanding what shapes users' trust in AI-generated health information (AI-HI) is essential. Despite growing use, little ... read more 

Chiral molecular assembly represents a frontier in creating life-inspired functional materials; yet, a predictive framework for its enantioselective catalysis remains elusive. Here, we introduce the Catassembly Triad - a mechanistic paradigm for cata... read more 

PurposeThis study aimed to assess the feasibility of artificial intelligence (AI)-based models for predicting recurrence risk and supporting individualized treatment strategies in pediatric pilonidal sinus disease (PSD).MethodsClinical data from 242 ... read more 

PurposeLong-term survival after endovascular aneurysm repair (EVAR) for abdominal aortic aneurysm remains a clinical concern, particularly in elderly patients with comorbidities. This study aimed to compare different machine learning (ML) models that... read more 

Neuromorphic computing is a bioinspired paradigm that emulates the structure and functionality of biological neural networks, demanding cutting-edge materials and device architectures. In this work, we present a bioinspired electrochemical neuromorph... read more