e.g. mhealth
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Skip search results from other journals and go to results- 31 Journal of Medical Internet Research
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Considering that disease notification by routine diagnostic activities imperfectly reflects the burden of disease in such populations, alternative case detection approaches are needed.
To this end, community-based active case-finding (ACF) can be an effective approach if targeted at high-risk subgroups or implemented with high coverage and intensity [1-5].
JMIR Public Health Surveill 2025;11:e68355
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DOR: diagnostic odds ratio.
Summary receiver operating characteristic curve for abnormal lung sound detection machine learning models. The solid black line represents the estimated summary receiver operating characteristic curve. The green triangle marks the pooled sensitivity and specificity estimated from the bivariate meta-analysis, with the 95% CI ellipse around it. Red dots represent the sensitivity and specificity of individual studies. DOR: diagnostic odds ratio.
J Med Internet Res 2025;27:e66491
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The diagnostic accuracies of GPT-4 Turbo and GPT-4o were 0.546 (95% CI 0.515‐0.577) and 0.577 (95% CI 0.547‐0.608), respectively. There was no significant difference in accuracy between the two models (P=.10). GPT-4 Turbo demonstrated a sensitivity of 76.3%, specificity of 32.9%, and false-positive rate of 67.1% (Table 1).
JMIR Dermatol 2025;8:e67551
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Noteworthy, MDW received approval from the Food and Drug Administration and European Community In-Vitro Diagnostic Medical Device as an early sepsis indicator in adult patients in the ED. MDW has great potential to be used in clinical practice because it is timely and fruitfully measured without further samples, additional costs, or even a different request from clinicians. Thus, it represents a cost-effective tool for early sepsis screening.
J Med Internet Res 2025;27:e55492
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Reference 32: Automatic identification of heart failure diagnostic criteria, using text analysis of clinical processing annotation tool to facilitate phenotyping of cognitive status in electronic health records: diagnosticdiagnostic
JMIR Aging 2025;8:e65221
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Families in rural or underserved areas can now access diagnostic services more easily through remote assessments [11]. In addition, telehealth can significantly reduce wait times by enabling quicker initial screenings and follow-ups, which is especially beneficial given the high demand for autism assessments and the limited number of specialists available [11]. Our recent systematic review found that Telehealth assessments are as accurate as in-person assessments, with over 80% diagnostic agreement [12].
JMIR Res Protoc 2025;14:e55741
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DL and ML approaches have been widely applied to various diagnostic tasks, although the diagnostic accuracy of DL remains uncertain in some areas. To address this gap, meta-analysis methods have been proposed [4] to provide a more comprehensive understanding. For example, studies have estimated the diagnostic accuracy of DL models for COVID-19 detection [5] and evaluated ML models for osteoporosis diagnosis in the hip bone [6].
J Med Internet Res 2025;27:e62647
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The diagnostic accuracy of uroflowmetry is largely affected by threshold values [12,13], especially with physiological compensatory processes, detrusor underactivity, or an underfilled bladder [14]. Although uroflowmetry can be used to monitor treatment outcomes [15] and to correlate symptoms with these objective findings [12,16], its clinical value is still limited, as it is unable to differentiate between the possible underlying mechanisms.
Interact J Med Res 2025;14:e66694
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A total of 2 reviewers (TW and NF) used the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2), which is a tool for assessing the quality of primary diagnostic accuracy studies, to independently assess the risk of bias for each eligible study [39]. The QUADAS-2 criteria assessed the risk of bias in 4 domains: patient selection, index test, reference standard, and flow and timing. Any disagreements were resolved by discussion with a third author.
J Med Internet Res 2024;26:e54676
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Large Language Models in Gastroenterology: Systematic Review
This, pivotal in diagnosing and treating digestive tract diseases, faces challenges like diagnostic variability and labor-intensive documentation. Gastrointestinal endoscopy, traditionally reliant on the expertise of specialists to interpret complex visual data and execute precise interventions, can greatly benefit from the automation and analytical capabilities provided by LLMs [4,5].
J Med Internet Res 2024;26:e66648
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