Search Articles

View query in Help articles search

Search Results (1 to 10 of 23 Results)

Download search results: CSV END BibTex RIS


Investigating Older Adults’ Perceptions of AI Tools for Medication Decisions: Vignette-Based Experimental Survey

Investigating Older Adults’ Perceptions of AI Tools for Medication Decisions: Vignette-Based Experimental Survey

One type of app may gather information from your electronic health record such as your health conditions and medications to create a personalized recommendation. The recommendation would be shared with your doctor for approval before your receive the information. [EHR-PCP] A second type of app may gather information from your electronic health record such as your health conditions and medications to create a personalized recommendation.

Sarah E Vordenberg, Julianna Nichols, Vincent D Marshall, Kristie Rebecca Weir, Michael P Dorsch

J Med Internet Res 2024;26:e60794

Clinical Use of Mental Health Digital Therapeutics in a Large Health Care Delivery System: Retrospective Patient Cohort Study and Provider Survey

Clinical Use of Mental Health Digital Therapeutics in a Large Health Care Delivery System: Retrospective Patient Cohort Study and Provider Survey

The first used a retrospective cohort design with KPNC EHR data to identify adult patients who were seen in the mental health department, diagnosed with a mental health disorder, and received a provider recommendation to a DTx, as well as a matched cohort of patients who were also seen in the mental health department with a diagnosed mental health disorder but did not receive a recommendation to a DTx. The second component consisted of an anonymous web-based survey of health system mental health providers.

Samuel J Ridout, Kathryn K Ridout, Teresa Y Lin, Cynthia I Campbell

JMIR Ment Health 2024;11:e56574

Artificial Intelligence–Augmented Clinical Decision Support Systems for Pregnancy Care: Systematic Review

Artificial Intelligence–Augmented Clinical Decision Support Systems for Pregnancy Care: Systematic Review

In this review, regression-based algorithms were widely used as benchmark algorithms for clinical prediction tools, diagnostic support, and therapeutants recommendation. Some of the studies used parametric linear statistical models as benchmarks [35]. Among supervised machine learning algorithms, support vector machine, random forest, and gradient boosting algorithms (eg, XGBoost) have been increasingly adopted and have revealed outstanding performance.

Xinnian Lin, Chen Liang, Jihong Liu, Tianchu Lyu, Nadia Ghumman, Berry Campbell

J Med Internet Res 2024;26:e54737

Digital Competencies and Training Approaches to Enhance the Capacity of Practitioners to Support the Digital Transformation of Public Health: Rapid Review of Current Recommendations

Digital Competencies and Training Approaches to Enhance the Capacity of Practitioners to Support the Digital Transformation of Public Health: Rapid Review of Current Recommendations

One recommendation was identified for basic literacy competencies specific to digital technologies regarding effectively communicating with teams through email, word processing, spreadsheets, and presentation software (communication) [32]. The 2 main categories of training approaches identified included recommendations for adapted degree-awarding programs and ongoing training or professional development. Most of the recommendations concerned adapting degree-awarding public health programs.

Swathi Ramachandran, Hsiu-Ju Chang, Catherine Worthington, Andre Kushniruk, Francisco Ibáñez-Carrasco, Hugh Davies, Geoffrey McKee, Adalsteinn Brown, Mark Gilbert, Ihoghosa Iyamu

JMIR Public Health Surveill 2024;10:e52798

Human-AI Teaming in Critical Care: A Comparative Analysis of Data Scientists’ and Clinicians’ Perspectives on AI Augmentation and Automation

Human-AI Teaming in Critical Care: A Comparative Analysis of Data Scientists’ and Clinicians’ Perspectives on AI Augmentation and Automation

ML can be utilized in the form of a “recommendation engine”, but doctors should never rely on it fully (DS 19). Besides the ethical issues of bias, transparency, and equity, some data science experts also felt that using AI in diagnostic decision-making would undermine physicians’ role identities, which could be problematic. This is what being a doctor is all about. Applying one’s knowledge and experience to diagnose patients is the very core of medicine.

Nadine Bienefeld, Emanuela Keller, Gudela Grote

J Med Internet Res 2024;26:e50130

Search Engines and Generative Artificial Intelligence Integration: Public Health Risks and Recommendations to Safeguard Consumers Online

Search Engines and Generative Artificial Intelligence Integration: Public Health Risks and Recommendations to Safeguard Consumers Online

(Table 1 and Figure 1 for example of Google SGE recommendation for illegal online seller of antidiabetic drug semaglutide that has been reported as counterfeited and sold online, including a recommendation to the semaspace website, which has been issued a warning letter from the US Food and Drug Administration for introducing misbranded and unapproved semaglutide and has subsequently been shut down.)

Amir Reza Ashraf, Tim Ken Mackey, András Fittler

JMIR Public Health Surveill 2024;10:e53086

Parents’ User Experience Accessing and Using a Web-Based Map of COVID-19 Recommendations for Health Decision-Making: Qualitative Descriptive Study

Parents’ User Experience Accessing and Using a Web-Based Map of COVID-19 Recommendations for Health Decision-Making: Qualitative Descriptive Study

Parents thought the website was easy to navigate, especially the home page, but found that it required several clicks to reach a specific health recommendation. Parents also found that navigating the recommendations in map view was challenging as many were unfamiliar with this format and required a few moments to understand what the headings and numbers signified (Figure S2 in Multimedia Appendix 3). Parents used a variety of navigation strategies when asked to find a recommendation specific to children.

Samantha Cyrkot, Lisa Hartling, Shannon D Scott, Sarah A Elliott

JMIR Form Res 2024;8:e53593