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Skip search results from other journals and go to results- 18 Journal of Medical Internet Research
- 13 JMIR Medical Informatics
- 7 JMIRx Med
- 5 JMIR Dermatology
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Although there are over 20 Food and Drug Administration (FDA)–approved AI applications for breast imaging, their adoption and utilization in clinical settings remain highly variable and generally low [6]. Significant barriers to the implementation of AI in breast screening include inconsistent performance, limited generalizability of AI algorithms across diverse scenarios, and a lack of confidence among health care providers.
J Med Internet Res 2025;27:e62941
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Moreover, other CVD manifestations, such as myocardial perfusion and mitochondrial dysfunction, may precede a myocardial injury detected by echocardiography; this can only be recognized by a higher level of imaging modalities, which use targeted radiotracers such as cardiac magnetic resonance imaging (CMR) and nuclear imaging to provide information on specific mechanisms of cardiotoxicity [24].
JMIR Cancer 2025;11:e63964
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Chadebec et al [1] have recently demonstrated, by using a VAE, that the artificial augmentation of medical imaging data significantly improved classification accuracy. The balanced accuracy increases from 66% to 74% for a convolutional neural network classifier trained with small datasets (50 magnetic resonance images each of cognitively healthy individuals and patients with Alzheimer disease), while improving greatly the sensitivity and specificity of the classification metrics [1].
J Med Internet Res 2025;27:e63130
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CNNs automatically extract and learn hierarchical features from grid-like data, such as images, and have achieved performance levels comparable to or surpassing those of human experts in various medical imaging domains [8]. In dermatological and wound imaging, CNNs have demonstrated promising results, matching or even exceeding the diagnostic accuracy of dermatologists in classifying skin cancer and other skin lesions [9].
JMIR Med Inform 2025;13:e62774
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However, techniques such as dual X-ray absorptiometry or body magnetic resonance imaging (MRI) are necessary to accurately assess lean or muscle mass. These methods can increase costs and time and are impractical in settings such as dementia clinics [6].
Dementia patients are highly affected by sarcopenia, with a prevalence of around 60%‐70% [7,8].
JMIR Aging 2025;8:e63686
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Using magnetic resonance imaging (MRI), physicians can diagnose a host of different pediatric conditions without exposing children to harmful ionizing radiation. Every year, millions of children get an MRI examination. To be able to have a successful examination, children need to enter a room with a large machine, lie down on a table that slides into this machine, and keep very still for an extended period of time (20-40 min, with some examinations taking up to an hour [1]).
JMIR Serious Games 2025;13:e55720
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For example, recent studies show the application of AI in cancer imaging analysis or in detecting acute intracranial hemorrhage on computed tomography (CT) or magnetic resonance imaging scans [18,19]. Similar studies have also shown promising results in the use of AI in the diagnosis of ischemic stroke (IS), with potential improvement of diagnostic accuracy and reduction of variability in the decision-making process. However, these studies all focus on the AI-based processing of visual information [18,20].
J Med Internet Res 2025;27:e48328
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Similarly, the National Institutes of Health has set up an “Imaging Data Commons” to provide secure access to a large collection of publicly available cancer imaging data colocated with analysis tools and resources [16]. Other researchers have shown that blockchain encryption technology can be used to securely store and share sensitive medical data [17].
JMIR AI 2025;4:e60847
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Lian et al [10] developed the FLAIR score, which includes 5 key indicators: ferritin levels, lactate dehydrogenase (LDH) levels, the anti-MDA5 antibody grade, the high-resolution computed tomography (HRCT) imaging score, and RP-ILD [10]. However, the FLAIR score was designed to predict mortality in patients with amyopathic DM.
J Med Internet Res 2025;27:e62836
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clinical outcomes among patients with acute low-risk pulmonary embolism and concerning computed tomography imagingimagingMedical imaging
JMIR Med Inform 2025;13:e58800
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