Showing 501 - 520 results of 664 for search '"medical imaging"', query time: 0.08s Refine Results
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    Angiographic Restenosis in Coronary Bifurcations Treatment with Regular Drug Eluting Stents and Dedicated Bifurcation Drug-Eluting BiOSS Stents: Analysis Based on Randomized POLBOS... by Robert J. Gil, Jacek Bil, Adam Kern, Luis A. Iñigo-Garcia, Radoslaw Formuszewicz, Slawomir Dobrzycki, Dobrin Vassilev, Roxana Mehran

    Published 2020-01-01
    “…Morphological pattern of in-stent restenosis according to the modified Mehran classification adopted for bifurcation lesions was assessed with bifurcation dedicated quantitative coronary angiographic software (CAAS 5.11, Pie Medical Imaging BV, the Netherlands). Results. In total, 445 patients (222 patients in BiOSS group and 223 patients in DES group) were included into the analysis. …”
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    Large Language Model Approach for Zero-Shot Information Extraction and Clustering of Japanese Radiology Reports: Algorithm Development and Validation by Yosuke Yamagishi, Yuta Nakamura, Shouhei Hanaoka, Osamu Abe

    Published 2025-01-01
    “…Clustering allows for the identification of similar lesions and disease patterns across a broad dataset, making it useful for aggregating information and discovering new insights in medical imaging. However, most publicly available medical datasets are in English, with limited resources in other languages. …”
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    Differences in technical and clinical perspectives on AI validation in cancer imaging: mind the gap! by Ioanna Chouvarda, Sara Colantonio, Ana S. C. Verde, Ana Jimenez-Pastor, Leonor Cerdá-Alberich, Yannick Metz, Lithin Zacharias, Shereen Nabhani-Gebara, Maciej Bobowicz, Gianna Tsakou, Karim Lekadir, Manolis Tsiknakis, Luis Martí-Bonmati, Nikolaos Papanikolaou

    Published 2025-01-01
    “…The work is based on a set of structured questions encompassing several AI validation topics, addressed to professionals working in AI for medical imaging. A total of 49 responses were obtained and analysed to identify trends and patterns. …”
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    Multimodal Magnetic Resonance Findings in Parkinson’s Disease With “Antecedent Essential Tremor”: A Case Series of a Large Kindred by Kong Y, Yao L, Xiao X, Chen A, Wang K, Yan H, Sun R, Liu R, Kong Q

    Published 2025-01-01
    “…Yu Kong,1,* Lei Yao,2,* Xiangyu Xiao,2,3 Anqiang Chen,1 Kexin Wang,1 Huan Yan,4 Ran Sun,4 Ruihan Liu,5,6,* Qingxia Kong4,* 1Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, Shandong, 272000, People’s Republic of China; 2Clinical Medical College, Jining Medical University, Jining, Shandong, 272000, People’s Republic of China; 3Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, People’s Republic of China; 4Department of Neurology, Affiliated Hospital of Jining Medical University, Jining, Shandong, 272029, People’s Republic of China; 5Department of Pediatrics, Affiliated Hospital of Jining Medical University, Jining, Shandong, 272029, People’s Republic of China; 6Postdoctoral Mobile Station of Shandong University of Traditional Chinese Medicine, Jinan, Shandong, 250012, People’s Republic of China*These authors contributed equally to this workCorrespondence: Qingxia Kong, Department of Neurology, Affiliated Hospital of Jining Medical University, 89 Guhuai Road, Jining, Shandong, 272000, People’s Republic of China, Email kxdqy8@sohu.com Ruihan Liu, Department of Pediatrics, Affiliated Hospital of Jining Medical University, 89 Guhuai Road, Jining, Shandong, 272000, People’s Republic of China, Email ruihanliu1987@163.comBackground: The clinical pictures of essential tremor (ET) and Parkinson’s disease (PD) are often quite mimic at the early stage, and longstanding ET may ultimately develop to PD, that is, PD with “antecedent ET”. …”
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    Hippocampal Functional Radiomic Features for Identification of the Cognitively Impaired Patients from Low-Back-Related Pain: A Prospective Machine Learning Study by Yang Z, Liang X, Ji Y, Zeng W, Wang Y, Zhang Y, Zhou F

    Published 2025-01-01
    “…Ziwei Yang,1,2,* Xiao Liang,1,2,* Yuqi Ji,1,2 Wei Zeng,1,2 Yao Wang,1,2 Yong Zhang,3 Fuqing Zhou1,2 1Jiangxi Provincial Key Laboratory for Precision Pathology and Intelligent Diagnosis, Department of Radiology, the First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, People’s Republic of China; 2Neuroradiology Laboratory, Jiangxi Province Medical Imaging Research Institute, Nanchang, 330006, People’s Republic of China; 3Department of Pain Clinic, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi Province, 330006, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yong Zhang, Department of Pain Clinic, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 17 Yongwaizheng Street, Nanchang, Jiangxi, 330006, People’s Republic of China, Tel +86 791 8869 5036, Email zy830226@163.com Fuqing Zhou, Jiangxi Provincial Key Laboratory for Precision Pathology and Intelligent Diagnosis, Department of Radiology, the First Affiliated Hospital, Jiangxi Medical College, Nanchang University, 17 Yongwaizheng Street, Nanchang, Jiangxi, 330006, People’s Republic of China, Tel +86 791 8869 5132, Email ndyfy02301@ncu.edu.cnPurpose: To investigate whether functional radiomic features in bilateral hippocampi can identify the cognitively impaired patients from low-back-related leg pain (LBLP).Patients and Methods: For this retrospective study, a total of 95 clinically definite LBLP patients (40 cognitively impaired patients and 45 cognitively preserved patients) were included, and all patients underwent functional MRI and clinical assessments. …”
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