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Background: An illness script is a specific script format geared to represent patient-oriented clinical knowledge organized around enabling conditions, faults (i.e., pathophysiological process), and consequences. Generative artificial intelligence (AI) stands out as an educational aid in continuing medical education. The effortless creation of a typical illness script by generative AI could help the comprehension of key features of diseases and increase diagnostic accuracy. No systematic summary of specific examples of illness scripts has been reported since illness scripts are unique to each physician., Objective: This study investigated whether generative AI can generate illness scripts., Methods: We utilized ChatGPT-4, a generative AI, to create illness scripts for 184 diseases based on the diseases and conditions integral to the National Model Core Curriculum in Japan for undergraduate medical education (2022 revised edition) and primary care specialist training in Japan. Three physicians applied a three-tier grading scale: "A" denotes that the content of each disease's illness script proves sufficient for training medical students, "B" denotes that it is partially lacking but acceptable, and "C" denotes that it is deficient in multiple respects., Results: By leveraging ChatGPT-4, we successfully generated each component of the illness script for 184 diseases without any omission. The illness scripts received "A," "B," and "C" ratings of 56.0% (103/184), 28.3% (52/184), and 15.8% (29/184), respectively., Conclusion: Useful illness scripts were seamlessly and instantaneously created using ChatGPT-4 by employing prompts appropriate for medical students. The technology-driven illness script is a valuable tool for introducing medical students to key features of diseases., (© 2024. The Author(s).)

Background: Medical history contributes approximately 80% to a diagnosis, although physical examinations and laboratory investigations increase a physician's confidence in the medical diagnosis. The concept of artificial intelligence (AI) was first proposed more than 70 years ago. Recently, its role in various fields of medicine has grown remarkably. However, no studies have evaluated the importance of patient history in AI-assisted medical diagnosis., Objective: This study explored the contribution of patient history to AI-assisted medical diagnoses and assessed the accuracy of ChatGPT in reaching a clinical diagnosis based on the medical history provided., Methods: Using clinical vignettes of 30 cases identified in The BMJ, we evaluated the accuracy of diagnoses generated by ChatGPT. We compared the diagnoses made by ChatGPT based solely on medical history with the correct diagnoses. We also compared the diagnoses made by ChatGPT after incorporating additional physical examination findings and laboratory data alongside history with the correct diagnoses., Results: ChatGPT accurately diagnosed 76.6% (23/30) of the cases with only the medical history, consistent with previous research targeting physicians. We also found that this rate was 93.3% (28/30) when additional information was included., Conclusions: Although adding additional information improves diagnostic accuracy, patient history remains a significant factor in AI-assisted medical diagnosis. Thus, when using AI in medical diagnosis, it is crucial to include pertinent and correct patient histories for an accurate diagnosis. Our findings emphasize the continued significance of patient history in clinical diagnoses in this age and highlight the need for its integration into AI-assisted medical diagnosis systems., (© Fumitoshi Fukuzawa, Yasutaka Yanagita, Daiki Yokokawa, Shun Uchida, Shiho Yamashita, Yu Li, Kiyoshi Shikino, Tomoko Tsukamoto, Kazutaka Noda, Takanori Uehara, Masatomi Ikusaka. Originally published in JMIR Medical Education (https://mededu.jmir.org).)

Okinawa prefecture is a popular tourist destination due to its beaches and reefs. The reefs host a large variety of animals, including a number of venomous species. Because of the popularity of the reefs and marine activities, people are frequently in close contact with dangerous venomous species and, thus, are exposed to potential envenomation. Commonly encountered venomous animals throughout Okinawa include the invertebrate cone snail, sea urchin, crown-of-thorns starfish, blue-ringed octopus, box jellyfish, and fire coral. The vertebrates include the stonefish, lionfish, sea snake, and moray eel. Treatment for marine envenomation can involve first aid, hot water immersion, antivenom, supportive care, regional anesthesia, and pharmaceutical administration. Information on venomous animals, their toxins, and treatment should be well understood by prehospital care providers and physicians practicing in the prefecture.

Matsutake mushrooms are among the best-known edible wild mushroom taxa worldwide. The representative Tricholoma matsutake is from East Asia and the northern and central regions of Europe. Here, we report the existence of T. matsutake under fir trees in Eastern Europe (i.e., Ukraine), as confirmed by phylogenetic analysis of nine loci on the nuclear and mitochondrial genomes. All specimens from Japan, Bhutan, China, North Korea, South Korea, Sweden, Finland, and Ukraine formed a T. matsutake clade according to the phylogeny of the internal transcribed spacer region. The European population of T. matsutake was clustered based on the β2 tubulin gene, with a moderate bootstrap value. In contrast, based on analyses of three loci, i.e., rpb 2, tef 1, and the β2 tubulin gene, T. matsutake specimens sampled from Bhutan and China belonged to a clade independent of the other specimens of this species, implying a genetically isolated population. As biologically available type specimens of T. matsutake have not been designated since its description as a new species from Japan in 1925, we established an epitype of this fungus, sampled in a Pinus densiflora forest in Nagano, Japan., (2022, by The Mycological Society of Japan.)