e.g. mhealth
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Skip search results from other journals and go to results- 99 Journal of Medical Internet Research
- 35 JMIR Research Protocols
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Furthermore, advanced imaging modalities and genomic data can be costly, with limited accessibility, and lack diversity and representativeness in samples, which could impact timely and accurate diagnosis for all individuals affected by EOCRC or widen already present disparities in patient outcomes.
In contrast to imaging and genomic data, structured data from the electronic health record (EHR) offers a more accessible and cost-effective data source for initial research.
JMIR Cancer 2025;11:e64506
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Individuals with normal circulatory findings and with no earlier diagnosis of diabetes or peripheral artery disease (PAD) were assigned to the healthy control group (n=98). All patients with diabetes, with or with no peripheral circulatory disturbance, were assigned to the group with diabetes (n=98). It is important to note that the group with diabetes did not have a visible foot ulcer. Approximately 61% (119/196) of participants were female, with a mean age of 39.2 (SD 15.5) years.
JMIR Diabetes 2025;10:e65209
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However, suboptimal follow-up and management of abnormal test results have been shown to contribute to delays in diagnosis [10].
Inadequate follow-up of abnormal test results may occur in the case of diagnostic errors, but is also influenced by the general practitioners’ (GPs) experience and training; perceptions of cancer care and investigations; patient characteristics; and health system pressures [11,12].
JMIR Cancer 2025;11:e65461
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Although this malignancy should represent 300‐480 cases (ie, 30%‐40% of all pediatric cancer diagnosis), only 40 cases per year have been seen over the last several years [5].
Number of cases of pediatric cancer diagnosed at Moi Teaching and Referral Hospital as a percentage of the expected total number of cases based on cancer epidemiology for the referral region.
JMIR Form Res 2025;9:e59776
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The application of ML and DL in leptospirosis diagnosis represents a significant advancement over traditional methods. ML algorithms can analyze clinical and laboratory data, including patient symptoms, demographic information, and test results, to predict the likelihood of leptospirosis.
JMIR Med Inform 2025;13:e67859
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The Infectious Diseases Society of America (IDSA) guidelines include SCI-specific signs and symptoms such as increased spasticity and autonomic dysreflexia [18] in their decision algorithms for UTI diagnosis [19], but limited evidence on the sensitivity and specificity of these symptoms exists.
Patients and providers alike have difficulty determining which signs and symptoms arise from UTI.
JMIR Res Protoc 2025;14:e52610
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As shown in Table 2, considering all the potential items that could be fulfilled by the apps for each domain, of the 27 apps selected, diagnosis and therapy support (90/513, 37%) and app technical characteristics (187/810, 23%) were the most frequently fulfilled domains, followed by AMS (13/162, 8%), pathogens and etiological agents (8/216, 4%), notes and records (5/162, 3%), network (4/189, 2%), AMR (2/162, 1%), and dashboard function (1/108, 1%).
JMIR Mhealth Uhealth 2025;13:e51122
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Numerous experts and scholars have explored the application of specialized AI and software tools in clinical diagnosis, yet there is limited knowledge about the performance of LLMs in this context. Therefore, this study aims to comprehensively evaluate the performance and accuracy of LLMs in clinical diagnosis, providing references for their clinical application.
JMIR Med Inform 2025;13:e64963
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The diagnosis of pathological conditions within the oral cavity has traditionally relied on visual examination, histopathological analysis, and clinical expertise [3]. However, AI algorithms have the potential to analyze various data sources, including clinical images, patient records, and radiographs, to provide valuable insights and suggestions for clinicians to facilitate the diagnosis of oral lesions [4].
Chat GPT is a recently introduced AI tool developed by Open AI.
JMIR AI 2025;4:e70566
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