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Plos One|March 6, 2023
Deep learning-based classification of adequate sonographic images for self-diagnosing deep vein thrombosisYusuke Nakayama, Mitsuru Sato, Masashi Okamoto, et al.Journal of X-Ray Science and Technology|June 29, 2024
Auto-evaluation of skull radiograph accuracy using unsupervised anomaly detectionHaruyuki Watanabe, Yuina Ezawa, Eri Matsuyama, et al.Biomedical Physics & Engineering Express|July 10, 2025
Recurrence prediction of invasive ductal carcinoma from preoperative contrast-enhanced computed tomography using deep convolutional neural networkManami Umezu, Yohan Kondo, Shota Ichikawa, et al.BMC Musculoskeletal Disorders|June 24, 2022
A deep convolutional neural network to predict the curve progression of adolescent idiopathic scoliosis: a pilot studyYasuhito Yahara, Manami Tamura, Shoji Seki, et al.Global Spine Journal|July 31, 2026
Development and Validation of a Multi-Modal Ensemble Model for Predicting Progression in Idiopathic ScoliosisHideyuki Arima, Shota Ichikawa, Yu Yamato, et al.Journal of Clinical Medicine|October 29, 2025
Development and Validation of Transformer- and Convolutional Neural Network-Based Deep Learning Models to Predict Curve Progression in Adolescent Idiopathic ScoliosisShinji Takahashi, Shota Ichikawa, Kei Watanabe, et al.Biomedical Physics & Engineering Express|June 21, 2022
Utility of U-Net for the objective segmentation of the fibroglandular tissue region on clinical digital mammogramsMika Yamamuro, Yoshiyuki Asai, Naomi Hashimoto, et al.Pageof 4