Search Articles

View query in Help articles search

Search Results (1 to 10 of 157 Results)

Download search results: CSV END BibTex RIS


Public Perception of the Brain-Computer Interface Based on a Decade of Data on X: Mixed Methods Study

Public Perception of the Brain-Computer Interface Based on a Decade of Data on X: Mixed Methods Study

We excluded posts before January 2010 due to limited data availability and after December 2021 to maintain the temporal consistency of the dataset, as our data cover only a few months of 2022 (Figure S1 in Multimedia Appendix 1). Detailed individual post data included the text, date and time of posts, the number of reposts, replies, likes, and quote count. Additional data included whether the post included links, media, tagging, or any hashtags.

Mohammed A Almanna, Lior M Elkaim, Mohammed A Alvi, Jordan J Levett, Ben Li, Muhammad Mamdani, Mohammed Al‑Omran, Naif M Alotaibi

JMIR Form Res 2025;9:e60859

Pursuit of Digital Innovation in Psychiatric Data Handling Practices in Ireland: Comprehensive Case Study

Pursuit of Digital Innovation in Psychiatric Data Handling Practices in Ireland: Comprehensive Case Study

With the growing reliance on digital health records, the risk of data-related threats continues to increase. In 2023 alone, European Union countries reported 309 major cybersecurity incidents in the health care sector, the highest among all critical sectors [5]. We have also listed some relevant incidents of data violations in Table 2. List of relevant data violation incidents.

Rana Zeeshan, John Bogue, Amna Gill, Mamoona Naveed Asghar

JMIR Hum Factors 2025;12:e64919

Alert Reduction and Telemonitoring Process Optimization for Improving Efficiency in Remote Patient Monitoring Programs: Framework Development Study

Alert Reduction and Telemonitoring Process Optimization for Improving Efficiency in Remote Patient Monitoring Programs: Framework Development Study

In 21st-century telemonitoring, patients measure relevant health data like vital signs at home according to a predefined measurement schedule [3]. These data are transmitted through a smartphone or tablet application, can be reviewed remotely by health care providers, and can trigger alerts based on pre-defined threshold values. Alerts are reviewed by e-nurses in remote patient monitoring centers and discussed with health care providers if required.

Job van Steenkiste, Niki Lupgens, Martijn Kool, Daan Dohmen, Iris Verberk-Jonkers

JMIR Med Inform 2025;13:e66066

Comparison of Deep Learning Approaches Using Chest Radiographs for Predicting Clinical Deterioration: Retrospective Observational Study

Comparison of Deep Learning Approaches Using Chest Radiographs for Predicting Clinical Deterioration: Retrospective Observational Study

Current EWS rely on structured data, such as vital signs and laboratory values, to predict clinical deterioration and ignore other data modalities that could potentially enhance prediction accuracy [7]. This results in lower detection and higher false-positive rates for these scores that could be mitigated by incorporating additional modalities [8].

Mahmudur Rahman, Jifan Gao, Kyle A Carey, Dana P Edelson, Askar Afshar, John W Garrett, Guanhua Chen, Majid Afshar, Matthew M Churpek

JMIR AI 2025;4:e67144

The AI Reviewer: Evaluating AI’s Role in Citation Screening for Streamlined Systematic Reviews

The AI Reviewer: Evaluating AI’s Role in Citation Screening for Streamlined Systematic Reviews

No personal or patient-level data were used, and no identifiers were included. Formal research ethics board approval was therefore not required. Among the 121 total citations, the LLMs’ sensitivity (correctly identifying included citations) ranged from 57% to 100%, and specificity (correctly excluding noneligible citations) ranged from 18% to 79%. Chat GPT 3.5 achieved the highest sensitivity (100%) and the highest specificity (79%). Full results are shown in Table 1.

Jamie Ghossein, Brett N Hryciw, Tim Ramsay, Kwadwo Kyeremanteng

JMIR Form Res 2025;9:e58366

Associations Among Online Health Information Seeking Behavior, Online Health Information Perception, and Health Service Utilization: Cross-Sectional Study

Associations Among Online Health Information Seeking Behavior, Online Health Information Perception, and Health Service Utilization: Cross-Sectional Study

An empirical analysis based on data from the United States Health Information Trends Survey revealed that OHIS has a positive, relatively large, and statistically significant effect on individual health care demand [21].

Hongmin Li, Dongxu Li, Min Zhai, Li Lin, ZhiHeng Cao

J Med Internet Res 2025;27:e66683

Assessing the Data Quality Dimensions of Partial and Complete Mastectomy Cohorts in the All of Us Research Program: Cross-Sectional Study

Assessing the Data Quality Dimensions of Partial and Complete Mastectomy Cohorts in the All of Us Research Program: Cross-Sectional Study

Accordingly, the primary objective of this study is to determine whether the All of Us data are fit for an analysis of women who had a mastectomy. The Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) is the data standard used by the All of Us Research Program. The OMOP CDM consists of standardized concepts and relationships, allowing for harmonizing data from different sources.

Matthew Spotnitz, John Giannini, Yechiam Ostchega, Stephanie L Goff, Lakshmi Priya Anandan, Emily Clark, Tamara R Litwin, Lew Berman

JMIR Cancer 2025;11:e59298

Assessing Digital Maturity of Hospitals: Viewpoint Comparing National Approaches in Five Countries

Assessing Digital Maturity of Hospitals: Viewpoint Comparing National Approaches in Five Countries

We assigned academic (KC, FJ, LW, TP, and EA) or policy (ML and SM) leads to each of the participating countries, who were responsible for collecting descriptive data. Using the nominal group technique with leads, we cocreated a data collection template table for each country, representing key features and learnings identified through discussions in group meetings.

Kathrin Cresswell, Franziska Jahn, Line Silsand, Leanna Woods, Tim Postema, Marion Logan, Sevala Malkic, Elske Ammenwerth

J Med Internet Res 2025;27:e57858

Empowering Health Care Actors to Contribute to the Implementation of Health Data Integration Platforms: Retrospective of the medEmotion Project

Empowering Health Care Actors to Contribute to the Implementation of Health Data Integration Platforms: Retrospective of the medEmotion Project

Accurate and well-formatted data are key to delivering high-quality health care and fueling medical research [1-3]. All health care actors acquire real-world data, defined as any health care-related information captured from the patient [4]. The volume, velocity, and variety of acquired data, however, raise challenges for data processing systems [5].

Marcel Parciak, Noëlla Pierlet, Liesbet M Peeters

J Med Internet Res 2025;27:e68083

Using Structured Codes and Free-Text Notes to Measure Information Complementarity in Electronic Health Records: Feasibility and Validation Study

Using Structured Codes and Free-Text Notes to Measure Information Complementarity in Electronic Health Records: Feasibility and Validation Study

EHR data are generally recorded in 2 forms: structured and unstructured data. Structured data includes clinical codes for documenting clinical events, such as diagnoses, medications, procedures, and measurements. Structured data is particularly suitable for observational research due to its consistent meaning, tabular format, and standardized vocabulary of codes.

Tom M Seinen, Jan A Kors, Erik M van Mulligen, Peter R Rijnbeek

J Med Internet Res 2025;27:e66910