e.g. mhealth
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Skip search results from other journals and go to results- 5 JMIRx Med
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Noninvasive imaging, such as mammography (MG), low-dose computed tomography (CT) for lung cancer screening (LCS), and CT colonography (CTC), plays important roles in the early detection of the most common cancer types and has demonstrated efficacy in reducing cancer-related and all-cause mortality rates [2,3].
JMIR Cancer 2025;11:e53328
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As shown in Figure 1, raw CT images of different types of cerebral hemorrhages were collected between January and September 2023 from the radiology database of Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine. Since GPT-4 cannot recognize continuous CT images, we first preprocessed the CT images. We chose the horizontal cranial CT image with the largest volume of hemorrhage in the brain window (window width: 90, window level: 35) as the representative image.
J Med Internet Res 2024;26:e58741
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Recently, a computed tomography (CT) scan estimation became a valid measure of standing WC [4,5]. This method is truly valuable in retrospective studies, where it can be difficult to obtain such measurements. Moreover, conventional WC assessment using a measurement tape can be challenging in patients with intellectual or motor disabilities. However, for a radiologist, this method may require time and training.
JMIRx Med 2023;4:e38852
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Response: Yes, indeed calculating the circumference using CT scan images has already been validated through many papers; however, what our study [2] is trying to do is create a simple and easy tool to retrospectively evaluate the WC using images from CTs, even real images from existing CT radio film papers (with a scale on it).
JMIRx Med 2023;4:e53817
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Although the manuscript makes a sound plausibility argument for the use of a smartphone app to determine WC from an existing computed tomography (CT) scan, it offers little rationale for using a pretreatment CT scan in preference to a conventional measurement with a tape measure or equivalent, especially as that measurement modality is taken as the comparison standard.
1. The authors admit that their conclusion is based on a very small sample of patients.
JMIRx Med 2023;4:e54045
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The authors created a mobile app that predicts waist circumference (WC) from computed tomography (CT) images [1]. After creating the app, the authors conducted a preliminary study involving 20 patients. The results showed that the developed app can predict WC from CT images with high accuracy. Though the paper showed some promising results, the authors still need to clarify a few important points. I hope the authors would be happy to clarify those points.
1.
JMIRx Med 2023;4:e54012
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Second, a data set was created using in-house CT reports annotated by medical experts. Third, state-of-the-art deep learning models were trained and evaluated to extract the clinical entities and relations. The entire performance of our 2-stage system was also evaluated. Finally, we evaluated the coverage of the clinical information in the CT reports using our information model.
The development of the information model was already reported in our previous study [27].
JMIR Med Inform 2023;11:e49041
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CT and MR exams were classified as “finding” if the radiologist entered one of the following options: “abnormal finding,” “urgent finding-24 hours,” “life-threatening finding.” Alternatively, CT and MR exams were labeled “no finding” if the radiologist entered “no finding” or “standard reporting that is not special.” The information on CT and MR exams also specified the organ system that was examined.
JMIR Form Res 2023;7:e42930
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Volumetric imaging with modalities like magnetic resonance imaging (MRI) or x-ray computed tomography (CT) has been a valuable tool in many areas of clinical, preclinical, and basic research. Image files are data rich, often with metadata containing (or linked to) both personal and sensitive data like the name of the participant or diagnoses.
J Med Internet Res 2022;24(11):e38650
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