orating artificial intelligence into the identification of epigenetic risk factors associated with HCM will promote accurate diagnosis and lead to the development of improved management plans, hence, positive patient outcomes. Furthermore, integration of these findings into the instructional design of undergraduate, postgraduate, and continuous professional development medical curricula will further contribute to the body of knowledge regarding HCM. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) PRR1-10.2196/17241. ©Nerissa Naidoo, Gurjyot Bajwa, Ruthwik Duvuru, Yajnavalka Banerjee. Originally published in JMIR Research Protocols (http//www.researchprotocols.org), 05.03.2020.BACKGROUND Serious educational games have shown effectiveness in improving various health outcomes. Previous reviews of health education games have focused on specific diseases, certain medical subjects, fixed target groups, or limited outcomes of interest. Given the recent surge in health game studies, a scoping review of health education games is needed to provide an updated overview of various aspects of such serious games. OBJECTIVE This study aimed to conduct a scoping review of the design and evaluation of serious educational games for health targeting health care providers, patients, and public (health) users. METHODS We identified 2313 studies using a unique combination of keywords in the PubMed and ScienceDirect databases. A total of 161 studies were included in this review after removing duplicates (n=55) and excluding studies not meeting our inclusion criteria (1917 based on title and abstract and 180 after reviewing the full text). The results were stratified based on games targeting health care pam Nazari, Hamed Tabesh, Maryam Edalati Khodabandeh, Somayeh Heidari, Mahmood Tara. Originally published in JMIR Serious Games (http//games.jmir.org), 05.03.2020.BACKGROUND Patients who suffer from different diseases may use different electronic health (eHealth) resources. Thus, those who plan eHealth interventions should take into account which eHealth resources are used most frequently by patients that suffer from different diseases. OBJECTIVE The aim of this study was to understand the associations between different groups of chronic diseases and the use of different eHealth resources. METHODS Data from the seventh survey of the Tromsø Study (Tromsø 7) were analyzed to determine how different diseases influence the use of different eHealth resources. Specifically, the eHealth resources considered were use of apps, search engines, video services, and social media. The analysis contained data from 21,083 participants in the age group older than 40 years. A total of 15,585 (15,585/21,083; 73.92%) participants reported to have suffered some disease, 10,604 (10,604/21,083; 50.29%) participants reported to have used some kind of eHealth resource in the last year, and 785eHealth resource may be used for gaining the attention of the different user groups. ©Luis Marco-Ruiz, Rolf Wynn, Sunday Oluwafemi Oyeyemi, Andrius Budrionis, Kassaye Yitbarek Yigzaw, Johan Gustav Bellika. Originally published in the Journal of Medical Internet Research (http//www.jmir.org), 05.03.2020.BACKGROUND Quality referrals to specialist care are key for prompt, optimal decisions about the management of patients with brain tumors. OBJECTIVE This study aimed to determine the impact of introducing a Web-based, electronic referral (eReferral) system to a specialized neuro-oncology center, using a service-developed proforma, in terms of waiting times and information completeness. METHODS We carried out a retrospective cohort study based on the review of medical records of referred adult patients, excluding follow-ups. Primary outcome measures were durations of three key phases within the referral pathway and completion rates of six referral fields. RESULTS A total of 248 patients were referred to the specialist center during the study period. Median (IQR) diagnostic imaging to referral intervals were 3 (1-5) days with eReferrals, and 9 (4-19), 19 (14-49), and 8 (4-23) days with paper proforma, paper letter, and internal referrals, respectively (P less then .001). Median (IQR) referral to multidisciplinarn than other referral types. A wider application of eReferrals is an important first step to streamlining specialist care pathways and providing excellent care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) RR2-10.2196/10.2196/15002. ©Rocío Fernández-Méndez, Mei Yin Wong, Rebecca J Rastall, Samuel Rebollo-Díaz, Ingela Oberg, Stephen J Price, Alexis J Joannides. Originally published in the Journal of Medical Internet Research (http//www.jmir.org), 05.03.2020.BACKGROUND The detection of dyskalemias-hypokalemia and hyperkalemia-currently depends on laboratory tests. Since cardiac tissue is very sensitive to dyskalemia, electrocardiography (ECG) may be able to uncover clinically important dyskalemias before laboratory results. OBJECTIVE Our study aimed to develop a deep-learning model, ECG12Net, to detect dyskalemias based on ECG presentations and to evaluate the logic and performance of this model. METHODS Spanning from May 2011 to December 2016, 66,321 ECG records with corresponding serum potassium (K+) concentrations were obtained from 40,180 patients admitted to the emergency department. ECG12Net is an 82-layer convolutional neural network that estimates serum K+ concentration. Six clinicians-three emergency physicians and three cardiologists-participated in human-machine competition. Sensitivity, specificity, and balance accuracy were used to evaluate the performance of ECG12Net with that of these physicians. RESULTS In a human-machine competition including 300inally published in JMIR Medical Informatics (http//medinform.jmir.org), 05.03.2020.BACKGROUND The internet is being widely used for seeking health information. However, there is no consensus on the association between health information seeking on the internet and the use of health care services. OBJECTIVE We examined the association between health information seeking via the internet and physician visits. In addition, we investigated the association between online health information seeking and the decisions to visit and not to visit a physician. METHODS We used the cross-sectional electronic health (eHealth) data of 18,197 participants from the seventh survey of the Tromsø Study (Tromsø 7). The participants were aged ≥40 years and living in Tromsø, Norway.  https://www.selleckchem.com/products/alpha-conotoxin-gi.html  We used logistic regression models to examine the association between online health information seeking and physician visits, the decision to visit a physician, and the decision not to visit a physician, with adjustment for the demographic status, socioeconomic status, and health status of the participants. RESULTS The use of Web search engines was associated with a physician visit.