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artificial intelligence

2023-03-29
29 March
On March 29, 2023
In Press Releases
Tagged artificial intelligence, chatbot, ChatGPT, conversational agent, education technology, generative pre-trained transformer, GPT, machine learning, medical education, MedQA, natural language processing, NLP

JMIR Medical Education | How does ChatGPT perform on the USMLE?

In a recent interview posted on JMIR TV, JMIR Publications’ CEO Dr Gunther Eysenbach speaks with Dr Andrew Taylor from Yale University School of Medicine about their paper titled “How Does ChatGPT Perform on the United States Medical Licensing Examination? The Implications of Large Language Models for Medical Education and Knowledge Assessment,” published in JMIR Medical Education.  The study examined how ChatGPT performed on the United States Medical Licensing Examination (USMLE) compared to other AI language models such as InstructGPT and GPT-3. The researchers found that ChatGPT’s performance on the exam was comparable to that of a third-year medical student in terms of medical knowledgeRead More →

2023-03-21
21 March
On March 21, 2023
In Press Releases
Tagged AI decision-making, artificial intelligence, health policy, health regulation, human decision-making, human roles, human-AI interaction, nonclinical health services

JMIR Research Protocols | What is the Role of Human Decision-making in an AI–driven Future in Health?

Australian researchers have established a set of protocols for a research project in JMIR Research Protocols  that aims to explore whether humans will continue in meaningful decision-making roles in an AI-driven future. The researchers, Dr Nandini Doreswamy and Dr Louise Horstmanshof from Southern Cross University, found that there is a dearth of guidance in establishing whole sets of protocols for methods used in complex health research. They have now established protocols that focus on non-clinical health services such as health regulation and health policy. These health services can be complex, the researchers say, and even more extensive in their scope and scale than clinical healthcare.Read More →

2023-03-16
16 March
On March 16, 2023
In Press Releases
Tagged artificial intelligence, creating images from text, DALL-E, diagnostic imaging, generative model, image creation, image generation, machine learning, medical imaging, radiology, text-to-image, transformer language model, x-ray

New Research Suggests AI Image Generation Using DALL-E 2 Has Promising Future in Radiology

A new paper published in the Journal of Medical Internet Research describes how generative models such as DALL-E 2, a novel deep learning model for text-to-image generation, could represent a promising future tool for image generation, augmentation, and manipulation in health care. Do generative models have sufficient medical domain knowledge to provide accurate and useful results? Dr Lisa C Adams and colleagues explore this topic in their latest viewpoint titled “What Does DALL-E 2 Know About Radiology?”  First introduced by OpenAI in April 2022, DALL-E 2 is an artificial intelligence (AI) tool that has gained popularity for generating novel photorealistic images or artwork based onRead More →

2023-03-03
03 March
On March 3, 2023
In Press Releases
Tagged artificial intelligence, chatbot, ChatGPT, conversational agent, education technology, generative pre-trained transformer, GPT, machine learning, medical education, MedQA, natural language processing, NLP

JMIR Medical Education Launches Special Issue on the Use of ChatGPT in Medical Education, After New Study Finds ChatGPT Passes the United States Medical Licensing Examination

A study published on February 8, 2023, in JMIR Medical Education, a leading open access journal on digital medical education, evaluated the potential of ChatGPT, a natural language processing model, as a medical education tool. The study found that ChatGPT reaches the equivalent of a passing score for a third-year medical student. Conducted by researchers from Yale University School of Medicine’s Section for Biomedical Informatics and Data Science and University College Dublin, the study aimed to test the performance of ChatGPT and previous-generation large language models on the medical question-answering problem as part of the United States Medical Licensing Examination (USMLE) Step 1 and StepRead More →

2022-12-07
07 December
On December 7, 2022
In Press Releases
Tagged artificial intelligence, automation, digital divide, digital health, eHealth, ethical, ethics, Future, hippocratic oath, medical perspective, moral, physician perspective, viewpoint

Journal of Medical Internet Research | Revised Hippocratic Oath for Digital Health

JMIR Publications published “A Revised Hippocratic Oath for the Era of Digital Health” in the Journal of Medical Internet Research, which argues that the Hippocratic Oath, which contains a set of ethical rules designed to guide physicians through their profession, should be updated to reflect the new realities of digital health and articulate updated principles that govern the practice of modern medicine. The original Hippocratic Oath still embodies ideals that are timely and relevant even in the 21st century: To treat patients to the best of one’s ability To preserve a patient’s privacy To faithfully teach the art of medicine to the next generation DespiteRead More →

2022-07-29
29 July
On July 29, 2022
In Press Releases
Tagged adapt, algorithm, artificial intelligence, behavior, behavioral science, chronic conditions, chronic disease, lifestyle, machine learning, prediction, self-care

JMIR Biomedical Engineering | Using Machine Learning to Reduce Treatment Burden

JMIR Publications recently published “Reducing Treatment Burden Among People With Chronic Conditions Using Machine Learning: Viewpoint” in JMIR Biomedical Engineering which reported that the COVID-19 pandemic has illuminated multiple challenges within the health care system and is unique to those living with chronic conditions. Recent advances in digital health technologies present opportunities to improve quality of care, self-management, and decision-making support to reduce treatment burden and the risk of chronic condition management burnout. There are limited available eHealth models that can adequately describe how this can be carried out. In this paper, the JMIR Biomedical Engineering authors define treatment burden and the related risk ofRead More →

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