Multimodal Deep Learning-based Radiomics Approach for Predicting Surgical Outcomes in Patients with Cervical Ossification of the Posterior Longitudinal Ligament

Satoshi Maki^*, Takeo Furuya, Keiichi Katsumi, Hideaki Nakajima, Kazuya Honjoh, Shuji Watanabe, Takashi Kaito, Shota Takenaka, Yuya Kanie, Motoki Iwasaki, Masayuki Furuya, Gen Inoue, Masayuki Miyagi, Shinsuke Ikeda, Shiro Imagama, Hiroaki Nakashima, Sadayuki Ito, Hiroshi Takahashi, Yoshiharu Kawaguchi, Hayato FutakawaKazuma Murata, Toshitaka Yoshii, Takashi Hirai, Masao Koda, Seiji Ohtori, Masashi Yamazaki

^*この論文の責任著者

整形外科・運動器病学講座

研究成果: ジャーナルへの寄稿 › 学術論文 › 査読

5 被引用数 (Scopus)

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Multimodal Deep Learning-based Radiomics Approach for Predicting Surgical Outcomes in Patients with Cervical Ossification of the Posterior Longitudinal Ligament

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Keyphrases

Medicine and Dentistry

Nursing and Health Professions

Biochemistry, Genetics and Molecular Biology

Neuroscience