Search Articles

View query in Help articles search

Search Results (1 to 10 of 478 Results)

Download search results: CSV END BibTex RIS


Improving Suicidal Ideation Detection in Social Media Posts: Topic Modeling and Synthetic Data Augmentation Approach

Improving Suicidal Ideation Detection in Social Media Posts: Topic Modeling and Synthetic Data Augmentation Approach

Our protocol was developed using the scoping review methodological framework proposed by Arksey and O’Malley [39] and further refined by Peters et al [40]. The central research question guiding this review was as follows: “What are the most frequently reported risk factors associated with suicidal ideation in the psychology and mental health literature?”

Hamideh Ghanadian, Isar Nejadgholi, Hussein Al Osman

JMIR Form Res 2025;9:e63272

Improving Patient Communication by Simplifying AI-Generated Dental Radiology Reports With ChatGPT: Comparative Study

Improving Patient Communication by Simplifying AI-Generated Dental Radiology Reports With ChatGPT: Comparative Study

In a recent meta-analysis by Armache et al [31], the readability of 1124 education materials for patients with head and neck cancer was evaluated that was produced by professional societies, hospitals, and other organizations intended to inform patients, promote their engagement, and enhance their adherence to treatment plans. The mean Flesch-Kincaid grade level of these materials ranged from 8.8 to 14.8, with none of them meeting the recommended sixth-grade readability standard.

Daniel Stephan, Annika S Bertsch, Sophia Schumacher, Behrus Puladi, Matthias Burwinkel, Bilal Al-Nawas, Peer W Kämmerer, Daniel GE Thiem

J Med Internet Res 2025;27:e73337

Sociodemographic and Socioeconomic Determinants for the Usage of Digital Patient Portals in Hospitals: Systematic Review and Meta-Analysis on the Digital Divide

Sociodemographic and Socioeconomic Determinants for the Usage of Digital Patient Portals in Hospitals: Systematic Review and Meta-Analysis on the Digital Divide

In a bivariate analysis and multivariate analysis by Balthazar et al [27], users were significantly more likely to be younger. Also, Holte et al [41], Hoogenbosch et al [24], Martinez et al [45], Plate et al [25], Owolo et al [48], and Ochoa et al [47] came to the same conclusion, that is, users were statistically and significantly younger than nonusers.

Nina Goldberg, Christin Herrmann, Paola Di Gion, Volker Hautsch, Klara Hefter, Georg Langebartels, Holger Pfaff, Lena Ansmann, Ute Karbach, Florian Wurster

J Med Internet Res 2025;27:e68091

Preferences and Willingness to Pay for Health App Assessments Among Health Care Stakeholders: Discrete Choice Experiment

Preferences and Willingness to Pay for Health App Assessments Among Health Care Stakeholders: Discrete Choice Experiment

The categorical variables were dummy coded using level 1 (as indicated in Figures 1 and 2) as the reference category (refer to the paper by Daly et al [43] for a discussion of effects coding vs dummy coding for choice models). The opt-out decisions, collected after the initial choice between assessments A and B, were incorporated into the analysis as recommended by Diener et al [44].

Anna-Lena Frey, Simon Leigh, Carla Toro, Carme Pratdepàdua Bufill, Charles McCay, Tatjana Prenđa Trupec, Giuseppe D'Avenio, Menno Kok, Antanas Montvila, Philipp Goedecker, Petra Hoogendoorn

JMIR Mhealth Uhealth 2025;13:e57474

Using WhatsApp for Nutrition Surveillance Among Children Under 5 Years in West Java, Indonesia: Cross-Sectional Survey and Feasibility Study

Using WhatsApp for Nutrition Surveillance Among Children Under 5 Years in West Java, Indonesia: Cross-Sectional Survey and Feasibility Study

In April and May, fewer results were entered due to Ramadan and Eid al-Fitr affecting how well cadres could input data. Toward the study’s end, a reminder was sent to cadres by DTO-Pusdatin Ministry of Health and village leaders about data entry. The comparison of total CU5 being measured and those reported through Whats App, and the linearity trend of total Whats App data reporting month by month. CU5: children under 5 years.

Dewi Nur Aisyah, Chyntia Aryanti Mayadewi, Astri Utami, Fauziah Mauly Rahman, Nathasya Humaira Adriani, Erlangga Al Farozi, Meldi Hafizh Sayoko, Aulia Chairunisa, Liza Restiana, Logan Manikam, Zisis Kozlakidis

JMIR Pediatr Parent 2025;8:e58752

Application of Artificial Intelligence in Cardio-Oncology Imaging for Cancer Therapy–Related Cardiovascular Toxicity: Systematic Review

Application of Artificial Intelligence in Cardio-Oncology Imaging for Cancer Therapy–Related Cardiovascular Toxicity: Systematic Review

In total, 7 studies conducted between 2018 and 2023 were included, with 5 from the United States (Kar et al [29-31], Zhang et al [32], Edalati et al [33]), 1 from China (Shen et al [34]), and 1 from Taiwan (Chang et al [35]). Of these, 6 studies involved patients with breast cancer with additional cancers (eg, sarcoma, lymphoma, leukemia) in some cohorts.

Hayat Mushcab, Mohammed Al Ramis, Abdulrahman AlRujaib, Rawan Eskandarani, Tamara Sunbul, Anwar AlOtaibi, Mohammed Obaidan, Reman Al Harbi, Duaa Aljabri

JMIR Cancer 2025;11:e63964