Kodai Kawaji, Masatoyo Nakajo, Yoshiaki Shinden, Megumi Jinguji, Atsushi Tani, Daisuke Hirahara, Ikumi Kitazono, Takao Ohtsuka, Takashi Yoshiura. Application of Machine Learning Analyses Using Clinical and [18F]-FDG-PET/CT Radiomic Characteristics to Predict Recurrence in Patients with Breast Cancer. Molecular imaging and biology. 2023. 25. 5. 923-934
Masatoyo Nakajo, Hiromi Nagano, Megumi Jinguji, Yoshiki Kamimura, Keiko Masuda, Koji Takumi, Atsushi Tani, Daisuke Hirahara, Keisuke Kariya, Masaru Yamashita, et al. The usefulness of machine-learning-based evaluation of clinical and pretreatment 18F-FDG-PET/CT radiomic features for predicting prognosis in patients with laryngeal cancer. The British journal of radiology. 2023. 96. 1149. 20220772-20220772
Daisuke Hirahara. [The Fundamentals of Diffusion Weighted Imaging (DWI) in the Mammary Region and Its Application to Artificial Intelligence (AI)]. Nihon Hoshasen Gijutsu Gakkai zasshi. 2023. 79. 11. 1310-1317
Takafumi Haraguchi, Yasuyuki Kobayashi, Daisuke Hirahara, Tatsuaki Kobayashi, Eichi Takaya, Mariko Takishita Nagai, Hayato Tomita, Jun Okamoto, Yoshihide Kanemaki, Koichiro Tsugawa. Radiomics model of diffusion-weighted whole-body imaging with background signal suppression (DWIBS) for predicting axillary lymph node status in breast cancer. Journal of X-ray science and technology. 2023. 31. 3. 627-640
Hayato Tomita, Tatsuaki Kobayashi, Eichi Takaya, Sono Mishiro, Daisuke Hirahara, Atsuko Fujikawa, Yoshiko Kurihara, Hidefumi Mimura, Yasuyuki Kobayashi. Deep learning approach of diffusion-weighted imaging as an outcome predictor in laryngeal and hypopharyngeal cancer patients with radiotherapy-related curative treatment: a preliminary study. European radiology. 2022. 32. 8. 5353-5361