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Use of Large Language Models to Classify Epidemiological Characteristics in Synthetic and Real-World Social Media Posts About Conjunctivitis Outbreaks: Infodemiology Study

Use of Large Language Models to Classify Epidemiological Characteristics in Synthetic and Real-World Social Media Posts About Conjunctivitis Outbreaks: Infodemiology Study

To ensure that our LLM-based approach for classifying conjunctivitis outbreaks can properly characterize such clinically important but rare events, we used an established solution in the field: we developed software code to generate preclassified synthetic posts to represent a full range of characteristics [54-58].

Michael S Deiner, Russell Y Deiner, Cherie Fathy, Natalie A Deiner, Vagelis Hristidis, Stephen D McLeod, Thomas J Bukowski, Thuy Doan, Gerami D Seitzman, Thomas M Lietman, Travis C Porco

J Med Internet Res 2025;27:e65226

Enhancing Magnetic Resonance Imaging (MRI) Report Comprehension in Spinal Trauma: Readability Analysis of AI-Generated Explanations for Thoracolumbar Fractures

Enhancing Magnetic Resonance Imaging (MRI) Report Comprehension in Spinal Trauma: Readability Analysis of AI-Generated Explanations for Thoracolumbar Fractures

A persistent limitation for AI-generated explanations, specifically in the medical field and radiology space, has been the inherent variability and occasional insufficiency of details in radiology reports [20]. As reported in this study, spine surgeons at times noted the lack of detail in Chat GPT-generated reports and cited this topic as an issue that needs to be addressed.

David C Sing, Kishan S Shah, Michael Pompliano, Paul H Yi, Calogero Velluto, Ali Bagheri, Robert K Eastlack, Stephen R Stephan, Gregory M Mundis Jr

JMIR AI 2025;4:e69654

Clinical Prediction Models Incorporating Blood Test Trend for Cancer Detection: Systematic Review, Meta-Analysis, and Critical Appraisal

Clinical Prediction Models Incorporating Blood Test Trend for Cancer Detection: Systematic Review, Meta-Analysis, and Critical Appraisal

For example, in the cancer field, the NICE guidelines recommend primary care to refer for cancer investigation if a patient’s risk is above 3%, which is often used to support referral of symptomatic patients, whose risk is likely higher than nonsymptomatic patients. For models derived for more general populations, such as the trend-based models included in this review, there is no clear cut-off.

Pradeep S Virdee, Kiana K Collins, Claire Friedemann Smith, Xin Yang, Sufen Zhu, Nia Roberts, Jason L Oke, Clare Bankhead, Rafael Perera, FD Richard Hobbs, Brian D Nicholson

JMIR Cancer 2025;11:e70275

Empowering Capabilities of People With Chronic Conditions Supported by Digital Health Technologies: Scoping Review

Empowering Capabilities of People With Chronic Conditions Supported by Digital Health Technologies: Scoping Review

Originally developed in the field of economics, the capability approach has gained traction in health care to conceptualize multidimensional constructs and evaluate health and social care interventions [30].

Messaline Fomo, Liyousew G Borga, Thomas Abel, Philip S Santangelo, Sara Riggare, Jochen Klucken, Ivana Paccoud

J Med Internet Res 2025;27:e68458

Associations Among Minority Stress, Allostatic Load, and Drug and Alcohol Use in Sexual Minorities: Protocol for the Queer Health Study—a Longitudinal Feasibility Evaluation

Associations Among Minority Stress, Allostatic Load, and Drug and Alcohol Use in Sexual Minorities: Protocol for the Queer Health Study—a Longitudinal Feasibility Evaluation

Next, field and range checks will be conducted. Distributional characteristics will be assessed and outliers will be checked. Prior to inferential procedures, extensive descriptive statistical analyses of the outcome and predictor variables will be conducted. Standard descriptive statistics including means, SDs, ranges, box plots, histograms, and frequencies will be calculated. Normalizing transformations will be explored as appropriate.

Nathan Grant Smith, Tzuan A Chen, Robert-Paul Juster, Ezemenari M Obasi, Jacob S Crocker

JMIR Res Protoc 2025;14:e73070

Assessing the Impact of Home Environmental Exposures on Allergic Rhinitis Using Real-Time Air Quality Monitoring and Symptom Assessment: Observational Feasibility Study

Assessing the Impact of Home Environmental Exposures on Allergic Rhinitis Using Real-Time Air Quality Monitoring and Symptom Assessment: Observational Feasibility Study

The field of measuring symptoms and air quality in real time in rhinitis is a nascent area, especially in minoritized populations that often have higher rates of exposure to rhinitis triggers [23]. Prior studies in real-time monitoring and rhinitis reviewed the existing research on EMA as a health monitoring tool and the use of ecological monitoring in understanding rhinitis symptoms and air quality both indoors and outdoors for individuals with asthma, but none focused on minoritized populations [19,24].

Aero Cavalier, Anthony I Dick, Vickie Johnson II, Emily Cramer, Kamal Eldeirawi, Jayant Pinto, Sharmilee M Nyenhuis, Victoria S Lee

JMIR Form Res 2025;9:e73215

A Customized Neural Transcranial Magnetic Stimulation Target for Functional Disability Among Veterans With Co-Occurring Alcohol Use Disorder and Mild Traumatic Brain Injury: Protocol for a Pilot Randomized Controlled Trial

A Customized Neural Transcranial Magnetic Stimulation Target for Functional Disability Among Veterans With Co-Occurring Alcohol Use Disorder and Mild Traumatic Brain Injury: Protocol for a Pilot Randomized Controlled Trial

BL: baseline visit; F1: follow-up time point visit occurring 2 weeks after the last active repetitive transcranial magnetic stimulation (r TMS) session; F2: follow-up time point visit occurring 1 month after the last active r TMS session; F3: follow-up time point visit occurring 3 months after the last active r TMS session; F4: follow-up time point visit occurring 6 months after the last active r TMS session; MT: motor threshold visit; PA: post–active r TMS visit; PS: post–sham r TMS visit; S: screening visit.

Amy A Herrold, Alexandra L Aaronson, Dulal Bhaumik, Timothy Durazzo, Sherri L Livengood, Alma Ramic, Patrick Riordan, Neil Jordan, Todd Parrish, Trudy Mallinson, Ibuola O Kale, Andrea Billups, Kelly Krese, Sandra Kletzel, Noah S Philip, Theresa L Bender Pape

JMIR Res Protoc 2025;14:e64909