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Background Digital health technologies hold promise to enhance patient-related outcomes, to support health care staff by reducing their workload, and to improve the coordination of care. As key users of digital health technologies, health care workers are crucial to enable a meaningful digital transformation of health care. Digital health literacy and digital skills should become prerequisite competencies for health professionals to facilitate the implementation and leverage the potential of digital technologies to improve health. Objective We aimed to assess European medical students’ perceived knowledge and opinions toward digital health, the status of digital health implementation in medical education, and the students’ most pressing needs. Methods The explanatory design of our mixed methods study was based on an online, anonymous, self-administered survey targeted toward European medical students. A linear regression analysis was used to identify the influence of the year of medical studies on the responses. Additional analysis was performed by grouping the responses by the self-evaluated frequency of eHealth technology use. Written responses to four qualitative questions in the survey were analyzed using an inductive approach. Results The survey received a total of 451 responses from 39 European countries, and there were respondents for every year of medical studies. The majority of respondents saw advantages in the use of digital health. While 40.6% (183/451) felt prepared to work in a digitized health care system, more than half (240/451, 53.2%) evaluated their eHealth skills as poor or very poor. Medical students considered lack of education to be the reason for this, with 84.9% (383/451) agreeing or strongly agreeing that more digital health education should be implemented in the medical curriculum. Students demanded introductory and specific eHealth courses covering data management, ethical aspects, legal frameworks, research and entrepreneurial opportunities, role in public health and health systems, communication skills, and practical training. The emphasis lay on tailoring learning to future job requirements and interprofessional education. Conclusions This study shows a lack of digital health-related formats in medical education and a perceived lack of digital health literacy among European medical students. Our findings indicate a gap between the willingness of medical students to take an active role by becoming key players in the digital transformation of health care and the education that they receive through their faculties.

Psoriasis is a chronic inflammatory skin disease showing a high burden due to its aesthetic, social, psychological, and quality of life (QoL) implications which also affect patient‐physician relationship and, consequently, the adherence to treatments. Limited data on the natural history of psoriasis and factors predicting its prognosis are available. The aim of this study was to investigate patients' global characteristics, including treatments, associated with QoL impairment in psoriasis. Questionnaires evaluating sociodemographic features and Dermatology Life Quality Index (DLQI) were administered to patients. Multiple regression analysis was performed to evaluate factors associated with a large effect on patient's life (DLQI > 10), moderate effect on patient's life (DLQI ≥ 6 ≤ 10), small effect on patient's life (DLQI ≥ 2 < 6), and no effect on patient's life (DLQI < 2). Overall, 1052 consecutive patients affected by mild‐to‐severe psoriasis were recruited. Our logistic regression analysis showed that the influencing factors for a large effect on QoL were living in Southern Italy, depression, psoriatic arthritis, and psoriasis localization on facial, intertriginous, palmoplantar, trunk and scalp regions. For a moderate effect on patient's life, phototherapy and non‐biological systemic therapies resulted to be the predictive factors. Mild psoriasis, living in social housing and the isolated involvement of scalp psoriasis had a small effect on QoL. Lastly, mild psoriasis and current biological therapies including anti‐IL‐12/23, anti‐IL‐17, and anti‐TNF‐α were positively associated with no life quality impairment. Perceived quality of life impairment in psoriasis not only depends on the skin disease but rather on patients' global characteristics. Therefore, the individual background of these patients should be respected in the selection of treatment options.

To better understand and interpret the trends in cutaneous research, we carried out a network analysis of all the titles of the submitted abstracts of the annual meetings of the European Society of Dermatological Research (ESDR), including the International Investigative Dermatology (IID) meetings between 2010 and 2019. Network analysis is a data science tool to process, analyze, and visualize big sets of data. As expected, psoriasis was the frontrunner in each of the annual meetings, followed by dermatitis and melanoma. Interestingly, alopecia, acne, squamous cell carcinoma, pruritus, basal cell carcinoma, and hidradenitis suppurativa were among the next most frequently named diseases and/or terms. We also looked at diversity to assess how broad the interest of the submitting community is and to identify whether "blockbusters" such as psoriasis and atopic dermatitis expand in expense of other interests. In contrast to our expectations, the diversity of submissions to the ESDR annual meetings remained high over the 10 years of our observation period. Interestingly, the diversity increased in the years of the IID, indicating an outreach to other research areas worldwide compared with the ESDR meetings. This is true for both 2013 in Edinburgh, UK, and 2018 in Orlando, USA. During these meetings, this rise in diversity was associated with a relative decrease of the three most often named diseases. Network analysis thus may be a useful tool for research societies like the ESDR to identify trends and allocate resources such as reviewers and sessions accordingly. In addition, it can serve as quality control monitoring whether the ESDR continues to offer a platform for all researchers in cutaneous biology or implements or focuses on emerging fields.

BACKGROUND Digital health technologies promise to enhance patient-related outcomes, to support the healthcare staff by reducing their workload and improve the coordination of care. As key users of digital health technologies, healthcare workers are crucial to enable a meaningful digital transformation of healthcare. Digital health literacy and digital skills are to become prerequisite competencies for health professionals to facilitate the implementation and leverage the potential of digital technologies to improve health. OBJECTIVE We aimed to assess European medical students’ perceived knowledge and opinions towards digital health, the status of digital health implementation in medical education, and the students’ most pressing needs. METHODS The explanatory design of our mixed-methods study was based on an online, anonymous, self-administered survey targeted towards European medical students. The quantitative analysis was performed using R statistical language; qualitative data was analyzed applying an inductive categorization approach using MaxQDA 2020 software. RESULTS The survey received a total of 451 responses from 39 European countries and all years of medical studies. The majority of respondents saw advantages in the use of digital health. More than half (53%) evaluated their eHealth skills as poor or very poor and 40% felt prepared to work in a digitized healthcare system. Medical students considered the reason for this a lack of education, with 85 % agreeing or strongly agreeing that digital health education should be more implemented in the medical curriculum. Students demanded introductory and specific eHealth courses covering data management, ethical aspects, legal frameworks, research and entrepreneurial opportunities,, its role in public health and health systems, communication skills, and practical training with eHealth technologies. The emphasis lay on tailoring learning to future job requirements and interprofessional education. CONCLUSIONS This study shows a lack of digital health-related formats in medical education and a perceived lack of digital (health) literacy among European medical students. Our findings indicate a gap between the willingness of medical students to take an active role by becoming key players in the digital transformation of healthcare, and the education they receive through their faculties. CLINICALTRIAL

Background Artificial intelligence (AI) and convolutional neural networks (CNNs) represent rising trends in modern medicine. However, comprehensive data on the performance of AI practices in clinical dermatologic images are non‐existent. Furthermore, the role of professional data selection for training remains unknown. Objectives The aims of this study were to develop AI applications for outlier detection of dermatological pathologies, to evaluate CNN architectures' performance on dermatological images and to investigate the role of professional pre‐processing of the training data, serving as one of the first anchor points regarding data selection criteria in dermatological AI‐based binary classification tasks of non‐melanoma pathologies. Methods Six state‐of‐the‐art CNN architectures were evaluated for their accuracy, sensitivity and specificity for five dermatological diseases and using five data subsets, including data selected by two dermatologists, one with 5 and the other with 11 years of clinical experience. Results Overall, 150 CNNs were evaluated on up to 4051 clinical images. The best accuracy was reached for onychomycosis (accuracy = 1.000), followed by bullous pemphigoid (accuracy = 0.951) and lupus erythematosus (accuracy = 0.912). The CNNs InceptionV3, Xception and ResNet50 achieved the best accuracy in 9, 8 and 6 out of 25 data sets, respectively (36.0%, 32.0% and 24.0%). On average, the data set provided by the senior physician and the data set provided in accordance with both dermatologists performed the best (accuracy = 0.910). Conclusions This AI approach for the detection of outliers in dermatological diagnoses represents one of the first studies to evaluate the performance of different CNNs for binary decisions in clinical non‐dermatoscopic images of a variety of dermatological diseases other than melanoma. The selection of images by an experienced dermatologist during pre‐processing had substantial benefits for the performance of the CNNs. These comparative results might guide future AI approaches to dermatology diagnostics, and the evaluated CNNs might be applicable for the future training of dermatology residents.

Visualising the past to plan the future: a network analysis of the largest European dermatology conference Background: The annual conference of the European Academy of Dermatology and Venereology is one the largest dermatology conferences worldwide. Objectives: Network analysis can be used for in-depth insight into trending topics and underlying trends at the congress. Materials & Methods: Network analysis was employed to assess the entirety of the submitted abstracts to the congress in 2019. The data were processed, analysed, and visualised using easy-to-understand network graphs. Topics were then compared to their respective global burden (Disease Adjusted Life Years [DALYs]) and the number of respective publications on PubMed in the year 2018. Results: Overall, 1,280 lecture titles and 1,941 poster titles were included in the final analysis. The most frequently used terms were "patients" (n = 473), "treatment" (n = 301), and "psoriasis" (n = 335). Relative to DALYs, "psoriasis" (+21.9%) among others, was rather over-represented, while "fungal skin diseases" (-7.6%) and "urticaria" (-6.4%) were under-represented. Compared to the relative number of PubMed publications in 2018, "psoriasis" (+20.3%), "acne" (+7.9%), and "alopecia" (+3.1%) were over-represented, while "melanoma" (-22.5%), "dermatitis" (-4.2%) and "pruritus" (-3.4%) were rather under-represented. Conclusion: The network analysis showed that the congress was a patient and therapy-centred event. An explanation for the particular focus on chronic inflammatory skin diseases and melanoma would be the introduction of new therapies at the congress. To delineate trends over time, a longitudinal network analysis including several congresses should be conducted and could be used to determine additional topics to be included in future events

Background Every two years, German-speaking dermatologic specialist groups gather in Berlin to share the latest developments at Germanýs largest dermatologic conference, the Annual Meeting of the Germany Society of Dermatology (DDG). Because this conference has a lasting effect on dermatologic practice and research, understanding what is moving the specialist groups means understanding what is driving dermatology in Germany. Methods We used word network analysis to compile and visualize the information embedded in the contribution titles to the DDG Annual Meeting in 2019. We extracted words, contributing cities and inter-connections. The data was standardized, visualized using network graphs and analyzed using common network analysis parameters. Results A total of 5509 words were extracted from 1150 contribution titles. The most frequently used words were “therapy”, “patients”, and “psoriasis”. The highest number of contributions came from Hamburg, Berlin and Munich. High diversity in research topics was found, as well as a well-connected research network. Conclusions Focus of the well-connected German-speaking dermatology community meeting 2019 was patient and therapy centered and lies especially on the diseases psoriasis and melanoma. Network graph analysis can provide helpful insights and help planning future congresses. It can facilitate the choice which contributors to include as imbalances become apparent. Moreover, it can help distributing the topics more evenly across the whole dermatologic spectrum.