e.g. mhealth
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Skip search results from other journals and go to results- 4 Journal of Medical Internet Research
- 3 JMIR Medical Informatics
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Examples include validation of optimal age-sex segmentation for CRC risk in a prospective cohort, incorporation of a comparison group without diabetes, exploration of the role of adiposity (general and abdominal) in CRC risk over the life course across sexes in a prospective cohort with a long-term follow-up, and new-user design in exploring drug effects (such as commonly used antidiabetic drugs and newer drugs including semaglutide) on CRC risk.
JMIR Public Health Surveill 2025;11:e62756
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However, SAM was primarily designed for 2 D image segmentation, which imposed inherent limitations on its direct applicability to 3 D volumetric data.
SAM 2, released in July 2024, introduced video segmentation capabilities [7], applicable to 3 D medical imaging like CT scans.
JMIR AI 2025;4:e72109
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Current NER tasks in the medical domain are primarily focused on Chinese NER, which presents a challenge due to unclear entity boundaries and difficulties in Chinese word segmentation, thereby undermining model performance.
Based on the above problems, this paper proposes a Segmentation Synonym Sentence Synthesis (SSSS) algorithm based on proximity lexical expressions, which was extensively validated on the China Conference on Knowledge Graph and Semantic Computing (CCKS) 2017 and 2019 datasets.
JMIR Med Inform 2024;12:e60334
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To this end, Hawkins et al [15] developed a framework in which the application of personalization and tailoring is described in terms of segmentation and customization. Segmentation is “the degree to which the audience is divided into increasingly more defined, homogenous groups,” a concept that originated in marketing [26].
J Med Internet Res 2024;26:e50497
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This is a peer-review report submitted for the preprint “A Hybrid Pipeline for Covid-19 Screening Incorporating Lungs Segmentation and Wavelet Based Preprocessing of Chest X-Rays.”
This review is the result of a live review organized and hosted by PREreview and JMIR Publications on September 2, 2022. The call was joined by 15 people, including reviewers, preprint authors, and facilitators.
JMIRx Med 2024;5:e64675
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Further, we discuss the conceptual value provided by the results from the development and validation of this market segmentation approach in the context of the broader market segmentation literature.
Market segmentation is a tool commonly applied to understand the attitudes, beliefs, and behaviors of homogenous subpopulations [9], which facilitates the development and placement of messages.
JMIR Public Health Surveill 2024;10:e56044
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Crowdsourcing data from a large number of nonexpert participants has been widely used for many medical applications [10,11], including bioinformatics [12], histology image labelling and cell segmentation [13-15], demarcating organs and regions of disease in both 2 D and 3 D radiology images [16,17], and combining crowd opinions with AI models for improving the severity scoring of diabetic retinopathy [18].
JMIR Dermatol 2023;6:e48589
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More specifically, this review aims to identify the common techniques that were developed to use Vi T for brain tumor segmentation and whether Vi Ts were effective in enhancing the segmentation performance. This review also identifies the common modality of brain imaging data used for training Vi T for brain tumor segmentation. Moreover, this review identifies the commonly used data sets for the brain tumor that contributed to developing Vi T-based models.
JMIR Med Inform 2023;11:e47445
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COVID-19 Mask Usage and Social Distancing in Social Media Images: Large-scale Deep Learning Analysis
There is no previous work trying to analyze mask fit using semantic segmentation to the best of our knowledge.
Therefore, this study fills the gap with a pipeline designed to estimate the extent of mask behaviors by assessing mask use and mask fit from 2.04 million social media images obtained from 6 US cities. Along with geographical diversity among the cities, the 6 cities also have high population numbers.
JMIR Public Health Surveill 2022;8(1):e26868
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Time-intensive manual segmentation and dose optimization steps can introduce delays to treatment.
Automated (ie, computer-performed) segmentation has the potential to address these challenges. However, most segmentation algorithms in clinical use are atlas based, producing segmentations by fitting previously labeled reference images to the new target scan.
J Med Internet Res 2021;23(7):e26151
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