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machine learning

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 →

2023-03-16
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 →

2022-07-29
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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