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Dermatologic Research in Displaced Populations: Importance, Challenges, and Proposed Solutions

Dermatologic Research in Displaced Populations: Importance, Challenges, and Proposed Solutions

Dermatologic conditions, not frequently prioritized in acute care settings, represent significant disease burden and often serve as visible markers of hygiene-related issues, systemic illness, or infectious outbreaks [3]. Infectious diseases such as malaria, measles, acute respiratory infections, and diarrheal illnesses are among the major causes of morbidity and mortality [4]. Along with malnutrition (particularly in children), these problems account for the majority of deaths among displaced persons [4].

Derek Maas, Jackleen S Marji

JMIR Dermatol 2025;8:e64828

Use of Retrieval-Augmented Large Language Model for COVID-19 Fact-Checking: Development and Usability Study

Use of Retrieval-Augmented Large Language Model for COVID-19 Fact-Checking: Development and Usability Study

The success of the RAG-equipped LLMs in enhancing the accuracy and efficiency of COVID-19 fact-checking suggests that similar approaches could be adapted and refined for broader applications, including emerging infectious diseases, cancer, cardiovascular health, and dietary behaviors [33,34]. Future research should explore the effectiveness of knowledge-graph RAG systems and the comparative performance of fine-tuned versus RAG-equipped LLMs in enhancing automated health fact-checking.

Hai Li, Jingyi Huang, Mengmeng Ji, Yuyi Yang, Ruopeng An

J Med Internet Res 2025;27:e66098

Oxidative Stress Markers and Prediction of Severity With a Machine Learning Approach in Hospitalized Patients With COVID-19 and Severe Lung Disease: Observational, Retrospective, Single-Center Feasibility Study

Oxidative Stress Markers and Prediction of Severity With a Machine Learning Approach in Hospitalized Patients With COVID-19 and Severe Lung Disease: Observational, Retrospective, Single-Center Feasibility Study

As a second analytical finding, we found that the SVM model could provide a prediction of the level of severity based on a biological analysis of the level of OS in a relatively limited cohort and during an epidemic of respiratory infectious disease, with only 7% misclassified cases in the training dataset. The originality of this work is the determination of the grade of clinical severity through the analysis of specific OS biomarkers using a machine learning model.

Olivier Raspado, Michel Brack, Olivier Brack, Mélanie Vivancos, Aurélie Esparcieux, Emmanuelle Cart-Tanneur, Abdellah Aouifi

JMIR Form Res 2025;9:e66509

Experiences of Public Health Professionals Regarding Crisis Communication During the COVID-19 Pandemic: Systematic Review of Qualitative Studies

Experiences of Public Health Professionals Regarding Crisis Communication During the COVID-19 Pandemic: Systematic Review of Qualitative Studies

Furthermore, the importance of rapid information dissemination was crucial in communication regarding a hitherto unknown infectious disease [11,15,39,44,47] (quotations 43 and 44). However, participants faced a dilemma whereby prioritizing the speed of communication did not allow sufficient time to create effective messages. For example, translation into multiple languages was time-consuming [11,44] (quotations 45 and 46).

Tsuyoshi Okuhara, Marina Terada, Hiroko Okada, Rie Yokota, Takahiro Kiuchi

JMIR Infodemiology 2025;5:e66524