AIMC Topic: Biomedical Research

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Quality and correctness of AI-generated versus human-written abstracts in psychiatric research papers.

Psychiatry research
This study aimed to assess the ability of an artificial intelligence (AI)-based chatbot to generate abstracts from academic psychiatric articles. We provided 30 full-text psychiatric papers to ChatPDF (based on ChatGPT) and prompted generating a simi...

Artificial intelligence methods available for cancer research.

Frontiers of medicine
Cancer is a heterogeneous and multifaceted disease with a significant global footprint. Despite substantial technological advancements for battling cancer, early diagnosis and selection of effective treatment remains a challenge. With the convenience...

Transforming Health Care Landscapes: The Lever of Radiology Research and Innovation on Emerging Markets Poised for Aggressive Growth.

Journal of the American College of Radiology : JACR
Advances in radiology are crucial not only to the future of the field but to medicine as a whole. Here, we present three emerging areas of medicine that are poised to change how health care is delivered-hospital at home, artificial intelligence, and ...

Understanding machine learning applications in dementia research and clinical practice: a review for biomedical scientists and clinicians.

Alzheimer's research & therapy
Several (inter)national longitudinal dementia observational datasets encompassing demographic information, neuroimaging, biomarkers, neuropsychological evaluations, and muti-omics data, have ushered in a new era of potential for integrating machine l...

Transformer models in biomedicine.

BMC medical informatics and decision making
Deep neural networks (DNN) have fundamentally revolutionized the artificial intelligence (AI) field. The transformer model is a type of DNN that was originally used for the natural language processing tasks and has since gained more and more attentio...

Bibliometric Analysis of Machine Learning Applications in Ischemia Research.

Current problems in cardiology
OBJECTIVE: The objective of this study is to conduct a comprehensive bibliometric analysis to elucidate the landscape of machine learning applications in ischemia research.

Biomedical Data Science, Artificial Intelligence, and Ethics: Navigating Challenges in the Face of Explosive Growth.

Annual review of biomedical data science
Advances in biomedical data science and artificial intelligence (AI) are profoundly changing the landscape of healthcare. This article reviews the ethical issues that arise with the development of AI technologies, including threats to privacy, data s...

Recommendations to promote fairness and inclusion in biomedical AI research and clinical use.

Journal of biomedical informatics
OBJECTIVE: Understanding and quantifying biases when designing and implementing actionable approaches to increase fairness and inclusion is critical for artificial intelligence (AI) in biomedical applications.