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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.
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Competência Clínica , Educação de Graduação em Medicina , Humanos , Japão , Inteligência Artificial , Currículo , Avaliação Educacional , Estudantes de MedicinaRESUMO
BACKGROUND: In Japan, postgraduate clinical training encompasses a 2-year residency program, including at least 24 weeks of internal medicine (IM) rotations. However, the fragmented structure of these rotations can compromise the training's quality and depth. For example, a resident might spend only a few weeks in cardiology before moving to endocrinology, without sufficient time to deepen their understanding or have clinical experience. This study examined current patterns and lengths of IM rotations within the Japanese postgraduate medical system. It scrutinized the piecemeal approach-whereby residents may engage in multiple short-term stints across various subspecialties without an overarching, integrated experience-and explored potential consequences for their clinical education. METHODS: This nationwide, multicenter, cross-sectional study used data from self-reported questionnaires completed by participants in the 2022 General Medicine In-Training Examination (GM-ITE). Data of 1,393 postgraduate year (PGY) one and two resident physicians who participated in the GM-ITE were included. We examined the IM rotation duration and number of IM subspecialties chosen by resident physicians during a 2-year rotation. RESULTS: Approximately half of the participants chose IM rotation periods of 32-40 weeks. A significant proportion of participants rotated in 5-7 internal medicine departments throughout the observation period. Notable variations in the distribution of rotations were observed, characterized by a common pattern where resident physicians typically spend 4 weeks in each department before moving to the next. This 4-week rotation is incrementally repeated across different subspecialties without a longer, continuous period in any single area. Notably, 39.7% of participants did not undertake general internal medicine rotations. These results suggest a narrowed exposure to medical conditions and patient care practices. CONCLUSIONS: Our study highlights the need to address the fragmented structure of IM rotations in Japan. We suggest that short, specialized learning periods may limit the opportunity to gain broad in-depth knowledge and practical experience. To improve the efficacy of postgraduate clinical education, we recommend fostering more sustained and comprehensive learning experiences.
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Internato e Residência , Médicos , Humanos , Estudos Transversais , Japão , Medicina Interna/educaçãoRESUMO
BACKGROUND: Physicians frequently experience patients as difficult. Our study explores whether more empathetic physicians experience fewer patient encounters as difficult. OBJECTIVE: To investigate the association between physician empathy and difficult patient encounters (DPEs). DESIGN: Cross-sectional study. PARTICIPANTS: Participants were 18 generalist physicians with 3-8 years of experience. The investigation was conducted from August-September 2018 and April-May 2019 at six healthcare facilities. MAIN MEASURES: Based on the Jefferson Scale of Empathy (JSE) scores, we classified physicians into low and high empathy groups. The physicians completed the Difficult Doctor-Patient Relationship Questionnaire-10 (DDPRQ-10) after each patient visit. Scores ≥ 31 on the DDPRQ-10 indicated DPEs. We implemented multilevel mixed-effects logistic regression models to examine the association between physicians' empathy and DPE, adjusting for patient-level covariates (age, sex, history of mental disorders) and with physician-level clustering. KEY RESULTS: The median JSE score was 114 (range: 96-126), and physicians with JSE scores 96-113 and 114-126 were assigned to low and high empathy groups, respectively (n = 8 and 10 each); 240 and 344 patients were examined by physicians in the low and high empathy groups, respectively. Among low empathy physicians, 23% of encounters were considered difficulty, compared to 11% among high empathy groups (OR: 0.37; 95% CI = 0.19-0.72, p = 0.004). JSE scores and DDPRQ-10 scores were negatively correlated (r = -0.22, p < 0.01). CONCLUSION: Empathetic physicians were less likely to experience encounters as difficult. Empathy appears to be an important component of physician perception of encounter difficulty.
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Relações Médico-Paciente , Médicos , Humanos , Estudos Transversais , Empatia , Inquéritos e QuestionáriosRESUMO
BACKGROUND: To investigate whether speech recognition software for generating interview transcripts can provide more specific and precise feedback for evaluating medical interviews. METHODS: The effects of the two feedback methods on student performance in medical interviews were compared using a prospective observational trial. Seventy-nine medical students in a clinical clerkship were assigned to receive either speech-recognition feedback (n = 39; SRS feedback group) or voice-recording feedback (n = 40; IC recorder feedback group). All students' medical interviewing skills during mock patient encounters were assessed twice, first using a mini-clinical evaluation exercise (mini-CEX) and then a checklist. Medical students then made the most appropriate diagnoses based on medical interviews. The diagnostic accuracy, mini-CEX, and checklist scores of the two groups were compared. RESULTS: According to the study results, the mean diagnostic accuracy rate (SRS feedback group:1st mock 51.3%, 2nd mock 89.7%; IC recorder feedback group, 57.5%-67.5%; F(1, 77) = 4.0; p = 0.049), mini-CEX scores for overall clinical competence (SRS feedback group: 1st mock 5.2 ± 1.1, 2nd mock 7.4 ± 0.9; IC recorder feedback group: 1st mock 5.6 ± 1.4, 2nd mock 6.1 ± 1.2; F(1, 77) = 35.7; p < 0.001), and checklist scores for clinical performance (SRS feedback group: 1st mock 12.2 ± 2.4, 2nd mock 16.1 ± 1.7; IC recorder feedback group: 1st mock 13.1 ± 2.5, 2nd mock 13.8 ± 2.6; F(1, 77) = 26.1; p < 0.001) were higher with speech recognition-based feedback. CONCLUSIONS: Speech-recognition-based feedback leads to higher diagnostic accuracy rates and higher mini-CEX and checklist scores. TRIAL REGISTRATION: This study was registered in the Japan Registry of Clinical Trials on June 14, 2022. Due to our misunderstanding of the trial registration requirements, we registered the trial retrospectively. This study was registered in the Japan Registry of Clinical Trials on 7/7/2022 (Clinical trial registration number: jRCT1030220188).
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Avaliação Educacional , Estudantes de Medicina , Humanos , Avaliação Educacional/métodos , Interface para o Reconhecimento da Fala , Estudos Retrospectivos , Competência ClínicaRESUMO
BACKGROUND: A clinical diagnostic support system (CDSS) can support medical students and physicians in providing evidence-based care. In this study, we investigate diagnostic accuracy based on the history of present illness between groups of medical students using a CDSS, Google, and neither (control). Further, the degree of diagnostic accuracy of medical students using a CDSS is compared with that of residents using neither a CDSS nor Google. METHODS: This study is a randomized educational trial. The participants comprised 64 medical students and 13 residents who rotated in the Department of General Medicine at Chiba University Hospital from May to December 2020. The medical students were randomly divided into the CDSS group (n = 22), Google group (n = 22), and control group (n = 20). Participants were asked to provide the three most likely diagnoses for 20 cases, mainly a history of a present illness (10 common and 10 emergent diseases). Each correct diagnosis was awarded 1 point (maximum 20 points). The mean scores of the three medical student groups were compared using a one-way analysis of variance. Furthermore, the mean scores of the CDSS, Google, and residents' (without CDSS or Google) groups were compared. RESULTS: The mean scores of the CDSS (12.0 ± 1.3) and Google (11.9 ± 1.1) groups were significantly higher than those of the control group (9.5 ± 1.7; p = 0.02 and p = 0.03, respectively). The residents' group's mean score (14.7 ± 1.4) was higher than the mean scores of the CDSS and Google groups (p = 0.01). Regarding common disease cases, the mean scores were 7.4 ± 0.7, 7.1 ± 0.7, and 8.2 ± 0.7 for the CDSS, Google, and residents' groups, respectively. There were no significant differences in mean scores (p = 0.1). CONCLUSIONS: Medical students who used the CDSS and Google were able to list differential diagnoses more accurately than those using neither. Furthermore, they could make the same level of differential diagnoses as residents in the context of common diseases. TRIAL REGISTRATION: This study was retrospectively registered with the University Hospital Medical Information Network Clinical Trials Registry on 24/12/2020 (unique trial number: UMIN000042831).
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Sistemas de Apoio a Decisões Clínicas , Médicos , Estudantes de Medicina , Humanos , Diagnóstico Diferencial , Hospitais UniversitáriosRESUMO
BACKGROUND: The pivot and cluster strategy (PCS) is a diagnostic reasoning strategy that automatically elicits disease clusters similar to a differential diagnosis in a batch. Although physicians know empirically which disease clusters are similar, there has been no quantitative evaluation. This study aimed to determine whether inter-disease distances between word embedding vectors using the PCS are a valid quantitative representation of similar disease groups in a limited domain. METHODS: Abstracts were extracted from the Ichushi Web database and subjected to morphological analysis and training using Word2Vec, FastText, and GloVe. Consequently, word embedding vectors were obtained. For words including "infarction," we calculated the cophenetic correlation coefficient (CCC) as an internal validity measure and the adjusted rand index (ARI), normalized mutual information (NMI), and adjusted mutual information (AMI) with ICD-10 codes as the external validity measures. This was performed for each combination of metric and hierarchical clustering method. RESULTS: Seventy-one words included "infarction," of which 38 diseases matched the ICD-10 standard with the appearance of 21 unique ICD-10 codes. When using Word2Vec, the CCC was most significant at 0.8690 (metric and method: euclidean and centroid), whereas the AMI was maximal at 0.4109 (metric and method: cosine and correlation, and average and weighted). The NMI and ARI were maximal at 0.8463 and 0.3593, respectively (metric and method: cosine and complete). FastText and GloVe generally resulted in the same trend as Word2Vec, and the metric and method that maximized CCC differed from the ones that maximized the external validity measures. CONCLUSIONS: The metric and method that maximized the internal validity measure differed from those that maximized the external validity measures; both produced different results. The cosine distance should be used when considering ICD-10, and the Euclidean distance when considering the frequency of word occurrence. The distributed representation, when trained by Word2Vec on the "infarction" domain from a Japanese academic corpus, provides an objective inter-disease distance used in PCS.
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Infarto , Humanos , Diagnóstico Diferencial , Análise por Conglomerados , Infarto/diagnósticoRESUMO
BACKGROUND: Patient awareness surveys on polypharmacy have been reported previously, but no previous study has examined the effects of sending feedback to health professionals on reducing medication use. Our study aimed to conduct a patient survey to examine factors contributing to polypharmacy, feedback the results to health professionals, and analyze the resulting changes in the number of polypharmacy patients and prescribed medications. METHODS: After conducting a questionnaire survey of patients in Study 1, we provided its results to the healthcare professionals, and then surveyed the number of polypharmacy patients and oral medications using a before-after comparative study design in Study 2. In Study 1, we examined polypharmacy and its contributing factors by performing logistic regression analysis. In Study 2, we performed a t-test and a chi-square test. RESULTS: In the questionnaire survey, significant differences were found in the following 3 items: age (odds ratio (OR) = 3.14; 95% confidence interval (CI) = 2.01-4.91), number of medical institutions (OR = 2.34; 95%CI = 1.50-3.64), and patients' difficulty with asking their doctors to deprescribe their medications (OR = 2.21; 95%CI = 1.25-3.90). After the feedback, the number of polypharmacy patients decreased from 175 to 159 individuals and the mean number of prescribed medications per patient decreased from 8.2 to 7.7 (p < 0.001, respectively). CONCLUSIONS: Providing feedback to health professionals on polypharmacy survey results may lead to a decrease in the number of polypharmacy patients. Factors contributing to polypharmacy included age (75 years or older), the number of medical institutions (2 or more institutions), and patients' difficulty with asking their physicians to deprescribe their medications. Feedback to health professionals reduced the percentage of polypharmacy patients and the number of prescribed medications. TRIAL REGISTRATION: UMIN. Registered 21 June 2020 - Retrospectively registered, https://www.umin.ac.jp/ctr/index-j.htm.
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Polimedicação , Retroalimentação , Humanos , Projetos Piloto , Inquéritos e QuestionáriosRESUMO
BACKGROUND: Training for the fundus examination using traditional teaching is challenging, resulting in low generalist physicians' confidence in performing the funduscopic examination. There is growing evidence suggesting a flexible e-learning video approach's value in teaching physical examination procedures. However, whether the flexible e-learning video approach is superior to the traditional, face-to-face (F2F) lecture-based teaching for the funduscopic exam and the cognitive processes supporting its effectiveness has not yet been determined. METHODS: We conducted a sequential explanatory mixed-method study to compare the flexible e-learning video approach's effectiveness versus the F2F lecture-based approach for teaching the funduscopic exam to medical students at Chiba University in Japan. Medical students were randomly assigned to either a flexible e-learning video approach group or a F2F lecture approach group. We then quantitatively measured the diagnostic accuracy of funduscopic findings before and after attending the specific classrooms. Next, we conducted student focus groups to explore the students' thinking processes in the flexible e-learning video approach vs. the F2F lecture-based teaching of fundus examination. The qualitative data were analyzed using the qualitative content analysis method. RESULTS: The mean diagnostic accuracy scores in the post-test significantly increased from pre-test in the intervention group (36.6 to 63.4%, p < 0.001). Post-post comparisons across the two groups revealed a significant difference (intervention group 63.4% vs. control group 34.6%, p < 0.001). Six semi-structured focused group interviews were conducted (n = 36). In the flexible e-learning video approach group, we identified ten categories corresponding to four levels of the revised Bloom's taxonomy: remember, understand, apply, analyze. Five categories were identified in the traditional F2F lecture approach group corresponding to three revised Bloom's taxonomy levels: understand, apply, analyze. Interrater reliability was substantial (Cohen's kappa = 0.81). CONCLUSIONS: Teaching medical students funduscopic examination using the flexible e-learning video approach leads to improved diagnostic accuracy of funduscopic examinations. The flexible e-learning video teaching method enabled higher cognitive activity levels than the traditional, lecture-based classroom, as assessed using the revised Bloom's taxonomy. TRIAL REGISTRATION: This study was registered with the University Hospital Medical Information Network Clinical Trials Registry on 08/02/2020 (Unique trial number: UMIN 000039434 ).
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Instrução por Computador , Estudantes de Medicina , Avaliação Educacional , Humanos , Aprendizagem , Reprodutibilidade dos Testes , EnsinoAssuntos
Eritromelalgia , Eritromelalgia/diagnóstico , Eritromelalgia/etiologia , Humanos , Dor/etiologiaRESUMO
Kikuchi-Fujimoto disease (KFD), also called histiocytic necrotizing lymphadenitis, is more common in young women and typically presents with small, painful, localized cervical lymphadenopathy that resolves spontaneously within a few weeks. Laboratory findings are variable. As many as 40% of KFD cases are reported to be painless, and up to 22% to be generalized lymphadenopathy. Therefore, malignant lymphoma could be a differential diagnosis of KFD. A histopathologic diagnosis is needed when it is difficult to distinguish KFD from lymphoma. KFD typically shows small, highly accumulated cervical lymph nodes on fluorodeoxyglucose positron emission tomography (FDG-PET). This contrasts with malignant lymphoma, which tends to be associated with massive lymphadenopathy. In our case, a 40-year-old Japanese male presented with painless lumps in the right neck, accompanied by fever, night sweats, and loss of appetite. His symptoms and laboratory results worsened over a month. FDG-PET revealed highly accumulated uptake in cervical, mediastinal, and axillary lymph nodes. The PET imaging showed a small, high FDG uptake and contributed to the correct diagnosis of KFD. This case report highlights the importance of FDG-PET, which is a valuable diagnostic tool for KFD as it typically differentiates large clusters of small lymph nodes typical of KFD from normal lymph nodes. LEARNING POINTS: Kikuchi-Fujimoto disease (KFD) typically presents with small, painful, localised cervical lymphadenopathy.KFD has atypical patterns showing painless and generalised lymphadenopathy.Fluorodeoxyglucose positron emission tomography (FDG-PET) could be useful for diagnosing not only malignant lymphoma but also KFD.
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This study tests whether comprehensively gathering information from medical records is useful for developing clinical decision support systems using Bayes' theorem. Using a single-center cross-sectional study, we retrospectively extracted medical records of 270 patients aged ≥16 years who visited the emergency room at the Tokyo Metropolitan Tama Medical Center with a chief complaint of experiencing headaches. The medical records of cases were analyzed in this study. We manually extracted diagnoses, unique keywords, and annotated keywords, classifying them as either positive or negative. Cross tables were created, and the proportion of combinations for which the likelihood ratios could be calculated was evaluated. Probability functions for the appearance of new unique keywords were modeled, and theoretical values were calculated. We extracted 623 unique keywords, 26 diagnoses, and 6,904 annotated keywords. Likelihood ratios could be calculated only for 276 combinations (1.70%), of which 24 (0.15%) exhibited significant differences. The power function+constant was the best fit for new unique keywords. The increase in the number of combinations after increasing the number of cases indicated that while it is theoretically possible to comprehensively gather information from medical records in this way, doing so presents difficulties related to human costs. It also does not necessarily solve the fundamental issues with medical informatics or with developing clinical decision support systems. Therefore, we recommend using methods other than comprehensive information gathering with Bayes' theorem as the classifier to develop such systems.
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BACKGROUND: Medical students in Japan undergo a 2-year postgraduate residency program to acquire clinical knowledge and general medical skills. The General Medicine In-Training Examination (GM-ITE) assesses postgraduate residents' clinical knowledge. A clinical simulation video (CSV) may assess learners' interpersonal abilities. OBJECTIVE: This study aimed to evaluate the relationship between GM-ITE scores and resident physicians' diagnostic skills by having them watch a CSV and to explore resident physicians' perceptions of the CSV's realism, educational value, and impact on their motivation to learn. METHODS: The participants included 56 postgraduate medical residents who took the GM-ITE between January 21 and January 28, 2021; watched the CSV; and then provided a diagnosis. The CSV and GM-ITE scores were compared, and the validity of the simulations was examined using discrimination indices, wherein ≥0.20 indicated high discriminatory power and >0.40 indicated a very good measure of the subject's qualifications. Additionally, we administered an anonymous questionnaire to ascertain participants' views on the realism and educational value of the CSV and its impact on their motivation to learn. RESULTS: Of the 56 participants, 6 (11%) provided the correct diagnosis, and all were from the second postgraduate year. All domains indicated high discriminatory power. The (anonymous) follow-up responses indicated that the CSV format was more suitable than the conventional GM-ITE for assessing clinical competence. The anonymous survey revealed that 12 (52%) participants found the CSV format more suitable than the GM-ITE for assessing clinical competence, 18 (78%) affirmed the realism of the video simulation, and 17 (74%) indicated that the experience increased their motivation to learn. CONCLUSIONS: The findings indicated that CSV modules simulating real-world clinical examinations were successful in assessing examinees' clinical competence across multiple domains. The study demonstrated that the CSV not only augmented the assessment of diagnostic skills but also positively impacted learners' motivation, suggesting a multifaceted role for simulation in medical education.
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Competência Clínica , Aprendizagem , Humanos , Estudos Transversais , Escolaridade , MotivaçãoRESUMO
Diagnosis and management of psychogenic diseases such as conversion disorder, somatic symptom disorder (SSD), illness anxiety disorder, falsehood disorder, and psychotic disorder require an elaborate biopsychosocial approach and are often challenging. Herein, we propose the following points to differentiate medical diseases from these psychogenic diseases: correspondence between symptoms and objective findings or activities of daily living (ADL) impairment; placebo effect; clear provocative or palliative factors; progressive time course; paroxysmal or intermittent symptoms; unfamiliar but not strange expressions; symptoms worsen during sleep or rest.
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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.
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Inteligência Artificial , Medicina , Humanos , Laboratórios , Processos Mentais , Exame FísicoRESUMO
Angina bullosa haemorrhagica (ABH) is a disease of unknown cause that occurs most frequently in middle-aged and older adults and is characterized by the destruction of blood vessels in the submucosal layer of the middle pharynx and larynx centred on the soft palate, resulting in the formation of haemorrhagic blisters. It usually resolves within a day and heals without scarring within about a week. No treatment is necessary. However, cases of airway obstruction due to haematemesis have been reported, and this potential risk should be considered when tracheal intubation or upper gastrointestinal endoscopy is being performed. In this report, we describe the case of a 50-year-old man who developed a haematoma in the pharynx following upper endoscopy, which spontaneously ruptured and healed, leading to the diagnosis of ABH. The main purpose of this case report is to remind the reader that ABH improves without treatment, thus eliminating the need for unnecessary examination, and that there is a risk of airway obstruction depending on the site of the lesion. LEARNING POINTS: The key to the diagnosis of angina bullosa haemorrhagica (ABH) is a history of acute haemorrhagic vesicles caused by an external stimulus such as food or intubation, which resolve without scarring within a week or so.ABH can occur at any oropharyngeal site, but its occurrence in the pharyngeal region raises the risk of airway obstruction due to haematemesis.
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OBJECTIVE: The pathophysiological concepts of diseases are encapsulated in patients' medical histories. Whether information on the pathophysiology or anatomy of "infarction" can be preserved and objectively expressed in the distributed representation obtained from a corpus of scientific Japanese medical texts in the "infarction" domain is currently unknown. Word2Vec was used to obtain distributed representations, meanings, and word analogies of word vectors, and this process was verified mathematically. MATERIALS & METHODS: The texts were abstracts that were obtained by searching for "infarction," "abstract," and "case report" in the Japan Medical Journal Association's Ichushi Data Base. The abstracted text was morphologically analyzed to produce word sequences converted into their standard form. MeCab was used for morphological analysis and mecab-ipadic-NEologd and ComeJisyo were used as dictionaries. The accuracy of the known tasks for medical terms was evaluated using a word analogy task specific to the "infarction" domain. RESULTS: Only 33 % of the word analogy tasks for medical terminology were correct. However, 52 % of the new original tasks, which were specific to the "infarction" domain, were correct, especially those regarding anatomical differences. DISCUSSION: Documents related to "infarction" were collected from a corpus of Japanese medical documents and word-embedded expressions were obtained using Word2Vec. Terminology that had similar meanings to "infarction" included words such as "cavity" and "ischemia," which suggest the pathology of an infarction. CONCLUSION: The pathophysiological and anatomical features of an "infarction" may be retained in a distributed representation.
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Infarto , Idioma , Terminologia como Assunto , Humanos , Bases de Dados Factuais , JapãoRESUMO
BACKGROUND: ChatGPT (OpenAI) has gained considerable attention because of its natural and intuitive responses. ChatGPT sometimes writes plausible-sounding but incorrect or nonsensical answers, as stated by OpenAI as a limitation. However, considering that ChatGPT is an interactive AI that has been trained to reduce the output of unethical sentences, the reliability of the training data is high and the usefulness of the output content is promising. Fortunately, in March 2023, a new version of ChatGPT, GPT-4, was released, which, according to internal evaluations, was expected to increase the likelihood of producing factual responses by 40% compared with its predecessor, GPT-3.5. The usefulness of this version of ChatGPT in English is widely appreciated. It is also increasingly being evaluated as a system for obtaining medical information in languages other than English. Although it does not reach a passing score on the national medical examination in Chinese, its accuracy is expected to gradually improve. Evaluation of ChatGPT with Japanese input is limited, although there have been reports on the accuracy of ChatGPT's answers to clinical questions regarding the Japanese Society of Hypertension guidelines and on the performance of the National Nursing Examination. OBJECTIVE: The objective of this study is to evaluate whether ChatGPT can provide accurate diagnoses and medical knowledge for Japanese input. METHODS: Questions from the National Medical Licensing Examination (NMLE) in Japan, administered by the Japanese Ministry of Health, Labour and Welfare in 2022, were used. All 400 questions were included. Exclusion criteria were figures and tables that ChatGPT could not recognize; only text questions were extracted. We instructed GPT-3.5 and GPT-4 to input the Japanese questions as they were and to output the correct answers for each question. The output of ChatGPT was verified by 2 general practice physicians. In case of discrepancies, they were checked by another physician to make a final decision. The overall performance was evaluated by calculating the percentage of correct answers output by GPT-3.5 and GPT-4. RESULTS: Of the 400 questions, 292 were analyzed. Questions containing charts, which are not supported by ChatGPT, were excluded. The correct response rate for GPT-4 was 81.5% (237/292), which was significantly higher than the rate for GPT-3.5, 42.8% (125/292). Moreover, GPT-4 surpassed the passing standard (>72%) for the NMLE, indicating its potential as a diagnostic and therapeutic decision aid for physicians. CONCLUSIONS: GPT-4 reached the passing standard for the NMLE in Japan, entered in Japanese, although it is limited to written questions. As the accelerated progress in the past few months has shown, the performance of the AI will improve as the large language model continues to learn more, and it may well become a decision support system for medical professionals by providing more accurate information.
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Purpose: This study aimed to investigate cancer screening rates and the reasons for not undergoing screening among patients who regularly visited the Sanmu Medical Center. Patients and Methods: This prospective observational study recruited patients aged ≥40 years with regular clinic visits to Sanmu Medical Center during October 2019. We conducted a self-administered survey to determine the patient's sex and whether they underwent cancer screening in 2019, and if not, the reason for the same. The primary outcome measure was the percentage of people who did not undergo cancer screening. Results: A total of 198 responses (108 male respondents) were obtained. Among them, 189 were valid responses (valid response rate 94.5%). One hundred and twenty-nine patients (68.2%, 76 male) had not undergone screening. The most common reasons provided were "I have regular regular clinic visits and do not think they are necessary" (N = 65, 50.3%), "I underwent a gastroscopy within 2 years, a colorectal camera examination within a few years, and a chest radiography within a year" (42.5%), and "I have a separate complete medical checkup" (N = 15, 11.6%). Of the 65 patients who responded that their cancer screenings were unnecessary, 42 patients (64.6%) had not undergone a gastroscopy within 2 years, a colorectal camera examination within a few years, or a chest radiography or examination within a year. Conclusion: Roughly half of the respondents who did not undergo cancer screening elected to abstain because they believed that regular hospital visits were sufficient. Encouraging patients who regularly visit medical institutions to receive cancer screening is therefore necessary.