AIMC Topic: Clinical Medicine

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A systematic review of large language model (LLM) evaluations in clinical medicine.

BMC medical informatics and decision making
BACKGROUND: Large Language Models (LLMs), advanced AI tools based on transformer architectures, demonstrate significant potential in clinical medicine by enhancing decision support, diagnostics, and medical education. However, their integration into ...

Performance of ChatGPT on Chinese Master's Degree Entrance Examination in Clinical Medicine.

PloS one
BACKGROUND: ChatGPT is a large language model designed to generate responses based on a contextual understanding of user queries and requests. This study utilised the entrance examination for the Master of Clinical Medicine in Traditional Chinese Med...

Performance of ChatGPT on the Chinese Postgraduate Examination for Clinical Medicine: Survey Study.

JMIR medical education
BACKGROUND: ChatGPT, an artificial intelligence (AI) based on large-scale language models, has sparked interest in the field of health care. Nonetheless, the capabilities of AI in text comprehension and generation are constrained by the quality and v...

Performance and exploration of ChatGPT in medical examination, records and education in Chinese: Pave the way for medical AI.

International journal of medical informatics
BACKGROUND: Although chat generative pre-trained transformer (ChatGPT) has made several successful attempts in the medical field, most notably in answering medical questions in English, no studies have evaluated ChatGPT's performance in a Chinese con...

Statistical methods for validation of predictive models.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Predictive models are widely used in clinical practice. Despite of the increasing number of published AI systems, recent systematic reviews have identified lack of statistical rigor in the development and validation of predictive models. This work re...

Application of AI and IoT in Clinical Medicine: Summary and Challenges.

Current medical science
The application of artificial intelligence (AI) technology in the medical field has experienced a long history of development. In turn, some long-standing points and challenges in the medical field have also prompted diverse research teams to continu...

Causality in digital medicine.

Nature communications
Ben Glocker (an expert in machine learning for medical imaging, Imperial College London), Mirco Musolesi (a data science and digital health expert, University College London), Jonathan Richens (an expert in diagnostic machine learning models, Babylon...

Systematic Review of Approaches to Preserve Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine.

Applied clinical informatics
OBJECTIVE: The change in performance of machine learning models over time as a result of temporal dataset shift is a barrier to machine learning-derived models facilitating decision-making in clinical practice. Our aim was to describe technical proce...

Editorial: Artificial Intelligence (AI) in Clinical Medicine and the 2020 CONSORT-AI Study Guidelines.

Medical science monitor : international medical journal of experimental and clinical research
Artificial intelligence (AI) in clinical medicine includes physical robotics and devices and virtual AI and machine learning. Concerns have been raised regarding ethical issues for the use of AI in surgery, including guidance for surgical decisions, ...