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Skip search results from other journals and go to results- 21 JMIR Formative Research
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In addition, studies often investigate the detection of texts written by chatbots using automatic tools or even detectors specifically designed for this purpose [18,25,27-30]. The detection rate of these detectors is often higher than that of human reviewers, but the accuracy can vary greatly depending on the text genre and the classifier used [14,31]. Moreover, linguistic features appear to be the most important subset of features influencing the performance of feature-based classifiers [2,5].
JMIR Med Educ 2025;11:e62779
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Therefore, early detection is fundamental to improving the patient outcome by promptly starting treatment. However, sepsis, especially in the early stage, may be characterized by nonspecific signs and symptoms, mainly when diagnosis of infection is still uncertain.
J Med Internet Res 2025;27:e55492
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Reference 7: Detection of atrial fibrillation in a large population using wearable devices: the fitbit Reference 10: Passive detection of atrial fibrillation using a commercially available smartwatch Reference 11: Accuracy and usability of a novel algorithm for detection of irregular pulse using a smartwatch Reference 18: Wearable sensor-based detection of influenza in presymptomatic and asymptomatic individualsdetection
JMIR Form Res 2025;9:e53645
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Despite the clear benefits of early detection and screening for reducing mortality rates, many individuals remain unaware of the importance of regular screenings and the risk factors associated with CRC [3-5]. March is designated as Colorectal Cancer Awareness Month, a period dedicated to increasing public knowledge about CRC, promoting early detection and screening, and ultimately reducing the incidence and mortality of this disease [6].
JMIR Form Res 2025;9:e63344
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The fields of health care and medical diagnostics have witnessed a significant shift toward noninvasive and accessible methods for early detection, assessment, and monitoring of medical conditions. This shift has been driven by technological advancements and growing research interest in digital health solutions [1]. Among these, speech analysis has emerged as a promising avenue, with studies identifying speech as a potential biosignature for a variety of neurodegenerative conditions [2,3].
JMIR Neurotech 2025;4:e64624
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Harnessing Internet Search Data as a Potential Tool for Medical Diagnosis: Literature Review
The table underscores the potential for leveraging search data across various medical domains to enhance diagnostic capabilities and early detection efforts.
A total of 16 interviews were conducted with participants from academic institutions (n=8, 50%), private-sector companies (n=5, 31%), and nonprofit organizations (n=3, 19%).
JMIR Ment Health 2025;12:e63149
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Even if patients prefer to wear sensors solely at the wrist, such as a stopwatch, or conceal them beneath clothing at the ankle or on a belt (lower back), as demonstrated by O’Day et al [15], the placement of sensors on multiple body parts could enhance the robustness of Fo G detection across various walking tasks and different Fo G subtypes.
JMIR Res Protoc 2025;14:e58612
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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]. Similarly, both ML and DL techniques have been extensively used for the detection and diagnostic evaluation of AD. Odusami et al [7] undertook a systematic review and meta-analysis. They used ML models alongside multimodal neuroimaging data to classify various stages of AD progression.
J Med Internet Res 2025;27:e62647
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Integrating PRO data with objective assessments within a smartphone app could achieve remote and objective CIPN monitoring and enhance the detection of CIPN with minimal inconvenience and cost [14].
J Med Internet Res 2025;27:e65615
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Oura Ring as a Tool for Ovulation Detection: Validation Analysis
The ovulation detection rate was defined as the proportion of ovulatory cycles in which the algorithm correctly identified an ovulation. We calculated the 95% CI for the detection rate using the z-score–based margin of error for proportions [36]. To assess statistical differences in the ovulation detection rate across subgroups, we used the Fisher exact test. This nonparametric statistical method is well-suited for comparing proportion data, especially in datasets where subgroups vary in sample size [37].
J Med Internet Res 2025;27:e60667
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