Anatomy-aware Self-supervised Learning for Anomaly Detection in Chest Radiographs. - Junya Sato; Yuki Suzuki; Tomohiro Wataya; Daiki Nishigaki; Kosuke Kita; Kazuki Yamagata; Noriyuki Tomiyama; Shoji Kido (CoRR, 2022)

Bi-modal network combining convolutional neural network and TabNet, differentiating spinal tumors based on images and clinical risk factors. - Kosuke Kita; Takahito Fujimori; Yuki Suzuki; Seiji Okada; Shoji Kido (Computer-Aided Diagnosis, 2023)

Automated entry of paper-based patient-reported outcomes: Applying deep learning to the Japanese orthopaedic association back pain evaluation questionnaire. - Kosuke Kita; Takahito Fujimori; Yuki Suzuki; Takashi Kaito; Shota Takenaka; Yuya Kanie; Masayuki Furuya; Tomohiro Wataya; Daiki Nishigaki; Junya Sato; Noriyuki Tomiyama; Seiji Okada; et al. (Comput. Biol. Medicine, 2024)

OURad at the NTCIR-18 RadNLP Task: Predicting Lung CancerClinical Staging from Radiology Reports Using Few-ShotPrompting of Large Language Models. - Junya Sato; Kosuke Kita; Daiki Nishigaki; Miyuki Tomiyama; Masatoshi Hori (NTCIR, 2025)

Comparison of active learning algorithms in classifying head computed tomography reports using bidirectional encoder representations from transformers. - Tomohiro Wataya; Azusa Miura; Takahisa Sakisuka; Masahiro Fujiwara; Hisashi Tanaka; Yu Hiraoka; Junya Sato; Miyuki Tomiyama; Daiki Nishigaki; Kosuke Kita; Yuki Suzuki; Shoji Kido; et al. (Int. J. Comput. Assist. Radiol. Surg., 2025)