Bioinformatics / Healthcare
Adaptation of deep learning to biotechnology/life science industry
PFN conducts R&D and drive commercialization of deep learning application for omics analysis, medical image analysis, and drug discovery.
- omics analysis: early cancer detection using miRNA
- medical image analysis: disease identification using X-ray, CT and MRI images
- Drug discovery: structure-based screening of potential compounds
We continue to expand and accelerate our research efforts in the field of Biomedical and Life Sciences.
Publications
Virtual Human Generative Model: Masked Modeling Approach for Learning Human Characteristics
arXiv preprint
By : Kenta Oono, Nontawat Charoenphakdee, Kotatsu Bito, Zhengyan Gao, Hideyoshi Igata, Masashi Yoshikawa, Yoshiaki Ota, Hiroki Okui, Kei Akita, Shoichiro Yamaguchi, Yohei Sugawara, Shin-ichi Maeda, Kunihiko Miyoshi, Yuki Saito, Koki Tsuda, Hiroshi Maruyama, Kohei Hayashi
Creating a general-purpose generative model for healthcare data based on multiple clinical studies
PLOS Digital Health
By : Hiroshi Maruyama, Kotatsu Bito, Yuki Saito, Masanobu Hibi, Shun Katada, Aya Kawakami, Kenta Oono, Nontawat Charoenphakdee, Zhengyan Gao, Hideyoshi Igata, Masashi Yoshikawa, Yoshiaki Ota, Hiroki Okui, Kei Akita, Shoichiro Yamaguchi, Yohei Sugawara, Shin-ichi Maeda
Scientific Reports
By : Rie Shiokawa, Junichiro Iwasawa, Yumiko Oishi Tanaka, Yuta Tokuoka, Yohei Sugawara, Yuichiro Hirano, Ryo Takaji, Yayoi Hayakawa, Keita Oda, Yasunori Kudo, Miho Li, Kazue Mizuno, Kazuhisa Ozeki, Ayako Nishimoto-Kakiuch, Kimio Terao
NeurIPS2024 AIM-FM workshop
By : Yuto Shibata, Yasunori Kudo, Yohei Sugawara
