Artificial intelligence-based education assists medical students’ interpretation of hip fracture

Abstract Background With recent transformations in medical education, the integration of technology to improve medical students’ abilities has become feasible. Artificial intelligence (AI) has impacted several aspects of healthcare. However, few studies have focused on medical education. We performed an AI-assisted education study and confirmed that AI can accelerate trainees’ medical image learning. Materials We developed an AI-based medical image learning system to highlight hip fracture on a plain pelvic film. Thirty medical students were divided into a conventional (CL) group and an AI-assisted learning (AIL) group. In the CL group, the participants received a prelearning test and a postlearning test. In the AIL group, the participants received another test with AI-assisted education before the postlearning test. Then, we analyzed changes in diagnostic accuracy. Results The prelearning performance was comparable in both groups. In the CL group, postlearning accuracy (78.66 ± 14.53) was higher than prelearning accuracy (75.86 ± 11.36) with no significant difference (p = .264). The AIL group showed remarkable improvement. The WithAI score (88.87 ± 5.51) was significantly higher than the prelearning score (75.73 ± 10.58, p < 0.01). Moreover, the postlearning score (84.93 ± 14.53) was better than the prelearning score (p < 0.01). The increase in accuracy was significantly higher in the AIL group than in the CL group. Conclusion The study demonstrated the viability of AI for augmenting medical education. Integrating AI into medical education requires dynamic collaboration from research, clinical, and educational perspectives.

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Endoscopic prediction of submucosal invasion in Barrett’s cancer with the use of Artificial Intelligence: A pilot Study

Endoscopy ◽

10.1055/a-1311-8570 ◽

2020 ◽

Author(s):

Alanna Ebigbo ◽

Robert Mendel ◽

Tobias Rückert ◽

Laurin Schuster ◽

Andreas Probst ◽

...

Keyword(s):

Artificial Intelligence ◽

Deep Learning ◽

Pilot Study ◽

White Light ◽

Submucosal Invasion ◽

Learning System ◽

Endoscopic Images ◽

Barrett’S Cancer ◽

Significant Difference ◽

Sensitivity Specificity

Background and aims: The accurate differentiation between T1a and T1b Barrett’s cancer has both therapeutic and prognostic implications but is challenging even for experienced physicians. We trained an Artificial Intelligence (AI) system on the basis of deep artificial neural networks (deep learning) to differentiate between T1a and T1b Barrett’s cancer white-light images. Methods: Endoscopic images from three tertiary care centres in Germany were collected retrospectively. A deep learning system was trained and tested using the principles of cross-validation. A total of 230 white-light endoscopic images (108 T1a and 122 T1b) was evaluated with the AI-system. For comparison, the images were also classified by experts specialized in endoscopic diagnosis and treatment of Barrett’s cancer. Results: The sensitivity, specificity, F1 and accuracy of the AI-system in the differentiation between T1a and T1b cancer lesions was 0.77, 0.64, 0.73 and 0.71, respectively. There was no statistically significant difference between the performance of the AI-system and that of human experts with sensitivity, specificity, F1 and accuracy of 0.63, 0.78, 0.67 and 0.70 respectively. Conclusion: This pilot study demonstrates the first multicenter application of an AI-based system in the prediction of submucosal invasion in endoscopic images of Barrett’s cancer. AI scored equal to international experts in the field, but more work is necessary to improve the system and apply it to video sequences and in a real-life setting. Nevertheless, the correct prediction of submucosal invasion in Barret´s cancer remains challenging for both experts and AI.

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Prevalence of somatic symptoms amongst undergraduate medical students of Marathwada region of Maharashtra, India

International Journal of Community Medicine and Public Health ◽

10.18203/2394-6040.ijcmph20205192 ◽

2020 ◽

Vol 7 (12) ◽

pp. 5106

Author(s):

Shaikh Arshiya Kaiser Husain ◽

Anwaya R. Magare ◽

Purushottam A. Giri ◽

Vijaykumar S. Jadhav

Keyword(s):

Medical Education ◽

Medical Students ◽

Medical Curriculum ◽

High Stress ◽

Well Being ◽

Undergraduate Medical Students ◽

Future Health ◽

Cross Sectional ◽

Significant Difference ◽

Negative Effect

Background: The aim of medical education is to produce competent, physically and mentally strong health professionals, as they are going to be the pillars of the future health care system. Stress is one of the most common and process-oriented obstacles in medical education. It often exerts a negative effect on the academic performance, physical health, and psychological well-being of the students. Dealing with overloaded medical curriculum, competing with peers, being away from home and meeting high expectations imposed by parents and society to excel is among the common stressful transitions at this stage.Methods: A cross-sectional descriptive study was carried out amongst 352 undergraduate medical students of a private medical college in a rural area of Maharashtra during April to October 2019. The structured questionnaire was used to record the data. Collected data was used to assess the severity of mental health issues among medical students.Results: Majority 194 (55.11%) students were in the age of 18 to 20 years followed by 141 (40.06%) were in 21 to 23 years. There were 196 (55.68%) girl students and 156 (44.32%) boys. According to the various categories, 80 (22.73%) of the students had low stress scores, followed by 76 (21.59%) in minimal. A highly significant difference in stress scores was seen between boys and girls, which was more in boys.Conclusions: Study concluded that undergraduate medical students perceive minimal to very high stress presented as various systems that vary with the year of study and gender wise too. There is a further need to look into the various causes of stress.

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Are We Ready to Integrate Artificial Intelligence Literacy into Medical School Curriculum: Students and Faculty Survey

Journal of Medical Education and Curricular Development ◽

10.1177/23821205211024078 ◽

2021 ◽

Vol 8 ◽

pp. 238212052110240

Author(s):

Elena A Wood ◽

Brittany L Ange ◽

D Douglas Miller

Keyword(s):

Artificial Intelligence ◽

Medical Education ◽

Medical Students ◽

Data Science ◽

School Curriculum ◽

Digital Data ◽

Technology Literacy ◽

Programming Approach ◽

Technology Applications ◽

The Media

Background: The effects of Artificial Intelligence (AI) technology applications are already felt in healthcare in general and in the practice of medicine in the disciplines of radiology, pathology, ophthalmology, and oncology. The expanding interface between digital data science, emerging AI technologies and healthcare is creating a demand for AI technology literacy in health professions. Objective: To assess medical student and faculty attitudes toward AI, in preparation for teaching AI foundations and data science applications in clinical practice in an integrated medical education curriculum. Methods: An online 15-question semi-structured survey was distributed among medical students and faculty. The questionnaire consisted of 3 parts: participant’s background, AI awareness, and attitudes toward AI applications in medicine. Results: A total of 121 medical students and 52 clinical faculty completed the survey. Only 30% of students and 50% of faculty responded that they were aware of AI topics in medicine. The majority of students (72%) and faculty (59%) learned about AI from the media. Faculty were more likely to report that they did not have a basic understanding of AI technologies (χ2, P = .031). Students were more interested in AI in patient care training, while faculty were more interested in AI in teaching training (χ2, P = .001). Additionally, students and faculty reported comparable attitudes toward AI, limited AI literacy and time constraints in the curriculum. There is interest in broad and deep AI topics. Our findings in medical learners and teaching faculty parallel other published professional groups’ AI survey results. Conclusions: The survey conclusively proved interest among medical students and faculty in AI technology in general, and in its applications in healthcare and medicine. The study was conducted at a single institution. This survey serves as a foundation for other medical schools interested in developing a collaborative programming approach to address AI literacy in medical education.

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Evaluating the appropriateness of electronic information resources for learning in pre-clerkship medical education : an eye tracking study

10.32469/10355/57780 ◽

2015 ◽

Author(s):

◽

Dinara Saparova

Keyword(s):

Medical Education ◽

Medical Students ◽

Learning Outcomes ◽

Mental Effort ◽

Information Resources ◽

First Year ◽

Electronic Information ◽

Electronic Information Resources ◽

Significant Difference ◽

First Year Medical Students

Current U.S. medical students have begun to rely on electronic information repositories -- such as UpToDate, Access Medicine, and Wikipedia -- for their pre-clerkship medical education. However, it is unclear whether these resources are appropriate for this level of learning due to factors involving information quality, level of evidence, and the requisite knowledge base. This study evaluated the appropriateness of electronic information resources from a novel perspective: the amount of mental effort learners invest in interactions with these resources and the effects of the experienced mental effort on learning. Eighteen first-year medical students read about three unstudied diseases in the three above-mentioned resources (a total of 54 observations). Their eye movement characteristics (i.e., fixation duration, fixation count, visit duration, and task-evoked pupillary response) were recorded and used as psychophysiological indicators of the experienced mental effort. Post reading, students' learning was assessed with a multiple-choice test. Eye metrics and test results constituted quantitative data that were analyzed according to the repeated Latin square design. Students' perceptions and observations of their interactions with the information resources constituted qualitative data that were also obtained. Participants' feedback from semi-structured interviews and recordings of students' information acquisition behaviors were reviewed, transcribed, and open coded for the emergent themes. Compared to Access Medicine and Wikipedia, UpToDate was associated with significantly higher values of eye metrics suggesting higher mental effort experienced by learners when using this resource. No statistically significant difference between the amount of mental effort and learning outcomes was found. More so, descriptive statistical analysis of the knowledge test scores suggested similar level of learning regardless of the information resource used. Students' feedback and observations of their behaviors were informative in understanding and interpreting the differences in quantitative findings. Judging by the learning outcomes, all three information resources were found appropriate for learning. UpToDate, however, when used alone, may be less appropriate for first-year medical students' learning as it does not fully address their information needs and is more demanding in terms of invested cognitive resources.

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Feedback to Receivers: Knowledge and Perception of Medical Students in a Public Sector Institute of a Developing Country

European Journal of Medical and Health Sciences ◽

10.24018/ejmed.2020.2.6.553 ◽

2020 ◽

Vol 2 (6) ◽

Author(s):

Hamza Waqar Bhatti ◽

Syed Muhammad Jawad Zaidi ◽

Mehwish Kaneez ◽

Javeria Awan ◽

Rashid Naeem Khan ◽

...

Keyword(s):

Medical Education ◽

Medical Students ◽

Developing Country ◽

Cross Sectional Study ◽

Cross Sectional ◽

Significant Difference ◽

Level Of Knowledge ◽

The Difference ◽

Medical University ◽

Feedback Delivery

Background: The practice of effective feedback delivery in medical institutes of developing countries lags behind the modern principles of medical education. This demands the need to understand the students’ knowledge and perception regarding received feedback in the setting of a developing country. Aims: To assess the level of knowledge and perception of feedback among students. To find the correlation between knowledge and perception. To identify problematic areas in feedback delivery and provide recommendations for rectification. Methods: A cross-sectional study conducted in Rawalpindi Medical University Pakistan, in which 480 medical students from 2nd till 5th-year MBBS were evaluated regarding their knowledge and perception about feedback using structured questionnaires. Results: The students had a good level of knowledge regarding The concept of feedback. However, they had a negative perception of the feedback given to them by their teachers. There was no correlation between mean knowledge and perception scores (r=-0.05, p = 0.272). There was a significant difference between knowledge (p=0.0004) and perception (p=0.02) scores across gender. The difference in mean knowledge scores across academic years was not significant (p=0.267) but this difference was significant for mean perception scores (p=0.001). Conclusion: Strategies should be adopted to incorporate feedback into the curriculum for improving the quality of medical education in a developing country.

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The PEGASUS Games: Physical Exam, Gross Anatomy, phySiology and UltraSound Games for Preclinical Medical Education

POCUS Journal ◽

10.24908/pocus.v6i1.14758 ◽

2021 ◽

Vol 6 (1) ◽

pp. 22-28

Author(s):

Mary Hennekes ◽

Sarah Rahman ◽

Andrea Schlosser ◽

Anne Drake ◽

Tessa Nelson ◽

...

Keyword(s):

Medical Education ◽

Medical Students ◽

Point Of Care ◽

Gross Anatomy ◽

Traditional Learning ◽

Point Of Care Ultrasound ◽

Learning Material ◽

Significant Difference ◽

Post Test ◽

Preclinical Medical Students

Introduction: Gamification engages learners and has successfully taught point-of-care ultrasound (POCUS) to residents and fellows. Yet ultrasound (US) curricula in undergraduate medical education remains limited. This study assessed a gamification model integrating US, anatomy, physiology, physical examination, and radiology created for preclinical medical students as compared with traditional didactic education. Methods: Twenty first-year medical students participated in a session on neck and thyroid material. Students were randomly assigned to a game or non-game group. Game students participated in games incorporating thyroid US with exam maneuvers, other imaging modalities, physiology, and pathology. Non-game students were taught the same material with an instructor. Students were assessed with a pretest and immediate and delayed post-tests. Group differences and scores were assessed using t-tests. A Likert scale evaluated learners’ opinions of the educational experience. Results: The game group performed better than the non-game group on the immediate post-test (p = 0.007, CI = [0.0305, ∞]). There was no significant difference between the groups on the delayed post-test (p = 0.726, CI = [-0.120, ∞]). Students in both groups felt more confident in their knowledge of the material, and all students in the game group agreed that the games encouraged teamwork. Most (9/10) stated the games allowed them to learn the material more effectively and would like to see more gamification (8/10). Conclusion: This US education model incorporating gamification for preclinical medical students promotes teamwork and is as effective for learning material than a traditional learning model. Students additionally convey a positive attitude towards gamification.

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Impact of COVID-19 pandemic on students’ performance in a problem-based learning system: comparative study between face-to-face-and virtual learning.

10.21203/rs.3.rs-114856/v1 ◽

2020 ◽

Author(s):

Tarik Al Shaibani ◽

Yahya Naguib ◽

Rima Abdul Razzak ◽

Fouad Ali

Keyword(s):

Medical Education ◽

Student Performance ◽

Arabian Gulf ◽

Learning System ◽

Face To Face ◽

Significant Difference ◽

Final Exams ◽

Ethical Approval ◽

Difficulty Index ◽

Teaching Learning

Abstract Background Amongst all other educational institutions, medical schools suffered the consequences of the COVID-19 pandemic. Medical education requires a great deal of interaction between instructors and students, and in the final years, patients as well. In response to the pandemic, the College of Medicine and Medical Sciences at the Arabian Gulf University has applied virtual teaching/learning since March 2020 as an alternative to face-to-face teaching. The college used Moodle and Zoom as online methods for education. The aim of the present study was to evaluate the effectiveness of virtual medical education by comparing students’ performance in final exams in face-to-face and virtual settings. Methods Following the college's ethical approval, this longitudinal study was performed on 183 medical students. Those students experienced 2 different successive methods of teaching/learning; Unit V as face-to-face followed by Unit VI as virtual settings. Students' performance in the final exams of both units was analyzed and compared. Results There was no significant difference in student performance between Units V and VI. Students' performance in the physiology part was equally effective in both units, while the difficulty index of both exams was insignificantly different. Conclusion Our results demonstrate that students’ performance in final exams could serve as an objective parameter when comparing different educational settings. Our results also support the idea that, in certain aspects, virtual is equal to face-to-face medical education strategies.

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The Role of Humanities in the Medical Curriculum: Medical Students’ Perspectives

10.21203/rs.3.rs-72841/v1 ◽

2020 ◽

Author(s):

Loukia Petrou ◽

Emma Mittelman ◽

Oluwapelumi Osibona ◽

Mona Panahi ◽

Joanna M Harvey ◽

...

Keyword(s):

Medical Education ◽

Medical Students ◽

Curriculum Design ◽

Medical Humanities ◽

Medical Curriculum ◽

School Curriculum ◽

Significant Difference ◽

Extracurricular Involvement ◽

Senior Students

Abstract BackgroundThe humanities have long been shown to play an important role in the medical school curriculum. However, few studies have looked into the opinions of medical students on the usefulness and necessity of the humanities as well as their extracurricular involvement with them. The aim of this study was to: a) understand medical students’ attitude towards the humanities in medical education and b) assess their understanding of the necessary qualities of doctors and how interaction with the humanities affects the development of such attributes. MethodsA mixed methods survey was designed to elicit demographics, engagement, interest and perspective on curricular positioning, and to explore how students ranked the qualities of a doctor. It was distributed to medical students of all year groups in the 6-year bachelor of medicine, bachelor of surgery (MBBS) course at Imperial College London. Results109 fully completed questionnaires were received. No significant difference was found in engagement or interest in the humanities between genders. Students felt strongly that humanities subjects shouldn’t be assessed (71:18) though some felt it was necessary for engagement, while no consensus was reached on whether these subjects should be elective or not (38:31). The majority of students wanted more medical humanities to be incorporated into the traditional medical course with a preference of incorporation into the first 3 years. Junior medical students were more likely to rank empathy as a highly desirable attribute than senior students. Students provided qualitative insights into curricular positioning, assessment and value.ConclusionsThis study provides the perspective of medical students on how and whether the humanities should be positioned in medical education. It may be helpful to medical schools that are committed to student involvement in curriculum design.

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Readiness to embrace artificial intelligence amongst medical doctors and students (Preprint)

10.2196/preprints.34973 ◽

2021 ◽

Author(s):

Thomas Boillat ◽

Faisal A. Nawaz ◽

Homero Rivas

Keyword(s):

Artificial Intelligence ◽

Medical Students ◽

P Value ◽

Medical Doctors ◽

New Paradigm ◽

Medical Outcomes ◽

Online Questionnaire ◽

Five Dimensions ◽

Low Level ◽

Significant Difference

BACKGROUND Similar to understanding how blood pressure is measured by a sphygmomanometer, physicians will soon have to understand how an Artificial Intelligence-based application has come to the conclusion that a patient suffers from hypertension, diabetes, or cancer. Though there is an increasing number of use cases where artificial intelligence is or can be applied to improve medical outcomes, the extent to which medical doctors and students are ready to work and leverage this paradigm is unclear. OBJECTIVE This research aims to capture medical students and doctors’ level of familiarity towards artificial intelligence in medicine as well as their challenges, barriers, and potential risks linked to the democratization of this new paradigm. METHODS An online questionnaire comprising five dimensions – demographics, concepts and definitions, training and education, implementation, and risks - was systematically designed from a literature search. It was filled in by 207 medical doctors and medical students trained in all continents with a majority of them in Europe, Middle East, Asia and North America. RESULTS Results revealed no significant difference in the familiarity of artificial intelligence between medical doctors and students (p-value=0.91), except that medical students perceived artificial intelligence in medicine to lead to higher risks for patients and the field of medicine in general (p-value=0.0006). We also identified a rather low level of familiarity with artificial intelligence (medical student=2.11/5; medical doctors=2.06/5) as well as a low attendance to education or training. Only 3/105 medical doctors attended a course on artificial intelligence within the last year compared to 10/102 medical students. Complexity of the field of medicine was considered as one of the biggest challenges (medical doctors=3.5/5; medical students 3.8/5) while the reduction of physicians’ skills the most important risk (medical doctors=3.3; medical students=3.6; p-value=0.031). CONCLUSIONS The question is not whether artificial intelligence will be used in medicine, but when it will become a standard practice for optimizing healthcare. The low level of familiarity with artificial intelligence identified in this study calls for the implementation of specific education and training in medical schools and hospitals to ensure that medical professionals can leverage this new paradigm and improve health outcomes.

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Diversity of Skin Images in Medical Texts: Recommendations for Student Advocacy in Medical Education

Journal of Medical Education and Curricular Development ◽

10.1177/23821205211025855 ◽

2021 ◽

Vol 8 ◽

pp. 238212052110258

Author(s):

Trisha Kaundinya ◽

Roopal V Kundu

Keyword(s):

Medical Education ◽

Medical Students ◽

Medical Image ◽

Scientific Literature ◽

Medical Texts ◽

Bottom Up ◽

Image Libraries ◽

Institutional Review ◽

Academic Medical ◽

Clinical Tools

Foundational academic medical texts facilitate foundational understanding of disease recognition in medical students. Significant underrepresentation of darker skin tones and overrepresentation of lighter skin tones in dermatologic texts, general medical texts, and scientific literature is observed. This compromises the clinical tools of trainees when it comes to darker skin tones. Text publishers and editors are steadily beginning to address these disparities, but bottom-up change from trainees is necessary to comprehensively address this issue. In this article the authors propose institutional review panels as a framework for building awareness of underrepresentation of darker skin tones and ensuring that faculty intentionally share diverse presentations in didactics. They also propose trainee engagement in building diverse medical image libraries and including texts on skin of color in institutional libraries. Empowering trainees to be advocates and call out any implicit or explicit biases in image selection can engender change in this area of medical education.

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