Twelve tips for medical students to conduct a systematic review.

Background: Medical students engaged in research develop general skills that are instrumental to clinical practice. The systematic review, a cornerstone of evidence-based medicine, represents an ideal starting point for student researchers. Aim and methods: To outline twelve tips on conducting a systematic review for medical students with limited research experience. Results: The tips in this article are practical, comprehensive, and informed by the authors experience as medical students. Conclusion: The twelve tips can help medical students contribute to the literature and build a valuable skillset for future research and clinical practice.

Deep Learning in Neuroradiology: A Systematic Review of Current Algorithms and Approaches for the New Wave of Imaging Technology.

PURPOSE: To systematically review and synthesize the current literature and to develop a compendium of technical characteristics of existing deep learning applications in neuroradiology. MATERIALS AND METHODS: A Preferred Reporting Items for Systematic Reviews and Meta-Analyses systematic review was conducted through September 1, 2019, using PubMed, Cochrane, and Web of Science databases. A total of 155 articles discussing deep learning applications in neuroimaging were identified, divided by imaging modality, and characterized by imaging task, data source, algorithm type, and outcome metrics. RESULTS: A total of 155 studies were identified and divided into: MRI (n = 115), functional MRI (n = 19), CT (n = 9), PET (n = 18), and US (n = 1). Seven were multimodal. MRI applications were described in 74%, and 76 (49%) were tasked with image segmentation. Of the 155 articles identified in this study, 65 (42%) were tested on institutional data; only 16 were validated against publicly available data. In addition, 53 studies (34%) used a combined dataset of less than 100, and 124 (80%) used a combined dataset of less than 1000. CONCLUSION: Although deep learning has demonstrated potential for each of these modalities, this review highlights several needs in the field of deep learning research including use of internal datasets without external validation, unavailability of implementation methods, inconsistent assessment metrics, and lack of clinical validation. However, the rapid growth of deep learning in neuroradiology holds promise and, as strides are made to improve standardization, generalizability, and reproducibility, it may soon play a role in clinical diagnosis and treatment of neurologic disorders.Supplemental material is available for this article.© RSNA, 2020.

Example-Based Learning as a Guide for Revising a Peer-Reviewed Manuscript.

Publishing medical research is an increasingly competitive process for junior researchers. One critical step is revising a manuscript with editorial team feedback. This article's purpose is to utilize a novel example-based learning approach to provide trainees and junior faculty with ten steps on how to successfully navigate the manuscript peer-review process. To this end, each step in the proposed guide is correlated with the authors' most recent publication experience, with key manuscript and editor response letter versions made available through an open-access digital repository.

Augmented reality in medical education: a systematic review.

INTRODUCTION: The field of augmented reality (AR) is rapidly growing with many new potential applications in medical education. This systematic review investigated the current state of augmented reality applications (ARAs) and developed an analytical model to guide future research in assessing ARAs as teaching tools in medical education. METHODS: A literature search was conducted using PubMed, Embase, Web of Science, Cochrane Library, and Google Scholar. This review followed PRISMA guidelines and included publications from January 1, 2000 to June 18, 2018. Inclusion criteria were experimental studies evaluating ARAs implemented in healthcare education published in English. Our review evaluated study quality and determined whether studies assessed ARA validity using criteria established by the GRADE Working Group and Gallagher et al., respectively. These findings were used to formulate an analytical model to assess the readiness of ARAs for implementation in medical education. RESULTS: We identified 100,807 articles in the initial literature search; 36 met inclusion criteria for final review and were categorized into three categories: Surgery (23), Anatomy (9), and Other (4). The overall quality of the studies was poor and no ARA was tested for all five stages of validity. Our analytical model evaluates the importance of research quality, application content, outcomes, and feasibility of an ARA to gauge its readiness for implementation. CONCLUSION: While AR technology is growing at a rapid rate, the current quality and breadth of AR research in medical training is insufficient to recommend the adoption into educational curricula. We hope our analytical model will help standardize AR assessment methods and define the role of AR technology in medical education.

CONTEXTE: Le domaine de la réalité augmentée (RA) est en pleine émergence et dispose de plusieurs nouvelles applications potentielles en éducation médicale. Cette revue systématique a évalué l'état actuel des applications de réalité augmentée (ARA) afin d'et élaboré un modèle analytique pour orienter les futures recherches sur l'évaluation des ARA comme outils pédagogiques en éducationmédicale. MÉTHODES: Une recherche documentaire a été menée à l'aide de PubMed, Web of Science, Cochrane Library et Google Scholar. Cette revue a suivi les directives de la méthode PRISMA et contenait les publications du 1er janvier 2000 au 18 juin 2018. Les études étaient retenues si elles avaient un devis expérimental et qu'elles avaient été publiées en anglais et qu'elles évaluaient des ARA mises en place dans l'enseignement des soins de santé. Notre revuea évalué la qualité des études et déterminé si les études ont pu évaluer la validité des ARA en utilisant les critères établis par le GRADE Working Group et Gallagher et coll., respectivement. À partir de ces conclusions, nous avons formulé un modèle analytique afin d'évaluer si les ARA peuvent être mises en place dans la formation médicale. RÉSULTATS: Nous avons trouvé 100 807 articles lors de la recherche documentaire initiale; 36 ont satisfait aux critères d'inclusion pour l'examen final et ont été classés dans trois catégories : chirurgie (23), anatomie (9) et autre (4). La qualité globaledes études était de mauvaise et aucune ARA n'a été testée pour toutes les cinq étapes de validité. Notre modèle analytique évalue l'importance de la qualité des recherches, du contenu des applications, des résultats, et de la faisabilité d'une ARA pour déterminer si elle est prête à être mise en place. CONCLUSION: Bien que la technologie de la RA progresse rapidement, la qualité et l'étendue actuelles de la recherche sur la RA en éducationmédicale sont insuffisantes pour recommander son adoption dans le cursus de formation. Nous espérons que notre modèle analytique aidera à uniformiserles méthodes d'évaluations de la RA et à déterminer le rôle de la technologie liée à la RA en éducation médicale.

A Potential Association Between Retinal Changes, Subjective Memory Impairment, and Anxiety in Older Adults at Risk for Alzheimer's Disease: A 27-Month Pilot Study.

INTRODUCTION: The utility of subjective memory impairment (SMI) as a risk marker for preclinical Alzheimer's disease (AD) remains unclear; however, recent studies have identified a correlation between retinal biomarkers and onset of preclinical disease. This study examines the relationship between retinal biomarkers that have been associated with cerebral amyloid, an early hallmark of AD, and SMI scores in patients at risk for developing AD. METHODS: Forty-nine cognitively normal subjects were followed over 27 months and evaluated using a combination of neuropsychological, psychological, and retinal imaging instruments. Subjective memory testing was conducted using the memory assessment clinic questionnaire (MACQ) and Depression, Anxiety, and Stress Scales (DASS). Multivariate linear analysis was conducted using STATA software. RESULTS: Positive correlations were found between retinal nerve fiber layer (RNFL) volume and scores obtained from the MAC-Q at 27 months (MAC-Q_27), the DASS questionnaire for anxiety at 27 months (DASS-A_27), and the change in DASS-A over 27 months (dDASSA). There was also a significant positive correlation between these variables and the change in RNFL thickness over 27 months (dRNFL). MACQ_27, DASSA_27, and dDASS-A accounted for 35.7% of RFNL variance at 27 months and 21.5% of dRFNL variance. DISCUSSION: These findings suggest that worse subjective memory complaints and anxiety scores may be associated with one of the most commonly used structural anatomical retinal markers of early disease burden in AD. If so, these results lend support to SMI as a valid risk marker for later cognitive decline.

Advances in Retinal Prosthetic Research: A Systematic Review of Engineering and Clinical Characteristics of Current Prosthetic Initiatives.

PURPOSE: To date, reviews of retinal prostheses have focused primarily on devices undergoing human trials in the Western Hemisphere and fail to capture significant advances in materials and engineering research in countries such as Japan and Korea, as well as projects in early stages of development. To address these gaps, this systematic review examines worldwide advances in retinal prosthetic research, evaluates engineering characteristics and clinical progress of contemporary device initiatives, and identifies potential directions for future research in the field of retinal prosthetics. METHODS: A literature search using PubMed, Google Scholar, and IEEExplore was conducted following the PRISMA Guidelines for Systematic Review. Inclusion criteria were peer-reviewed papers demonstrating progress in human or animal trials and papers discussing the prosthetic engineering design. For each initiative, a description of the device, its engineering considerations, and recent clinical results were provided. RESULTS: Ten prosthetic initiatives met our inclusion criteria and were organized by stimulation location. Of these initiatives, four have recently completed human trials, three are undergoing multi- or single-center human trials, and three are undergoing preclinical animal testing. Only the Argus II (FDA 2013, CE 2011) has obtained FDA approval for use in the United States; the Alpha-IMS (CE 2013) has achieved the highest visual acuity using a Landolt-C test to date and is the only device presently undergoing a multicenter clinical trial. CONCLUSION: Several distinct approaches to retinal stimulation have been successful in eliciting visual precepts in animals and/or humans. However, many clinical needs are still not met and engineering challenges must be addressed before a retinal prosthesis with the capability to fully and safely restore functional vision can be realized.