e.g. mhealth
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Skip search results from other journals and go to results- 5 Journal of Medical Internet Research
- 3 JMIR Formative Research
- 2 JMIR Medical Informatics
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- 1 JMIR Mental Health
- 1 JMIR mHealth and uHealth
- 1 Online Journal of Public Health Informatics
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In these scenarios, thoughtful and controlled techniques designed to generate inexact data are needed to reduce precision [12,16].
To this end, geospatial or location-based privacy methods seek to maintain an appropriate level of confidentiality for a given task, service, or application while balancing the utility that these offer [17-19].
Online J Public Health Inform 2024;16:e54958
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There are 2 common metrics for measuring usage prediction: precision and recall. Precision measures how likely it is that a recommended item is relevant and is defined as the ratio of relevant selected items to the total number of selected items [49]. Recall, conversely, measures how likely it is that a relevant item is selected and is defined as the ratio of relevant selected items to the total number of relevant items [49].
JMIR Ment Health 2024;11:e45754
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Reference 21: OncoKB: a precision oncology knowledge base Reference 29: The Molecular Tumor Board Portal supports clinical decisions and automated reporting for precisionprecision medicine precision
JMIR Med Inform 2023;11:e50017
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The Potential of ChatGPT as a Self-Diagnostic Tool in Common Orthopedic Diseases: Exploratory Study
In addition to accuracy, it is equally important to evaluate precision, since it is challenging to rely on a self-diagnostic tool that provides inconsistent answers across different days and users. Additionally, an AI chatbot is not a substitute for medical care and should appropriately recommend seeking medical consultation after self-diagnosis. However, there is no research evaluating both the precision of Chat GPT’s responses and the degree to which it recommends medical attention.
J Med Internet Res 2023;25:e47621
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The performance of the model was evaluated based on accuracy, precision, recall, F score, and area under the receiver operating characteristic curve (AUC; based on the test set), which were widely used in other studies [37-39]. The 95% CI of the AUC was calculated with bootstrapping, using 1000 iterations. Moreover, a decision curve analysis (DCA) was performed to evaluate the clinical utility of the 5 best performance prediction models by quantifying the net benefits.
Flowchart summary of our methodology.
J Med Internet Res 2023;25:e43815
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For each cutoff score, sensitivity (true positive rate) with upper and lower 95% CI, specificity (true negative rate) with 95% CI, precision (positive predictive value), and accuracy were reported.
A feasibility and clinical utility questionnaire was used to capture the assessors’ assessments of how easy each scale was to use and how well it performed (Table 1).
J Med Internet Res 2023;25:e41992
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Research focused on technology (ie, accuracy and precision) is of great interest, whereas studies of WAMs in the context of treatment and in medical settings have also been increasing. A recent systematic review [7] that analyzed 463 studies demonstrated a significant growth rate in the annual number of publications that included WAMs between 2013 and 2017. Measurement accuracy is a vital consideration, as WAMs are frequently used as a tool in research and a way of advising health care decisions.
JMIR Mhealth Uhealth 2022;10(8):e37547
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There are currently no agreed-upon protocols for machine learning models in precision health [44,45], and a number of different models have been used as frameworks for machine learning training and development [46]. Further, there is no well-defined approach to estimate carbohydrate intake, the effect of stress and activity on blood glucose level, or the portability of machine learning models to capture inter- and intraindividual variability [45,47].
JMIR Diabetes 2022;7(2):e34624
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