Bioinformatics / Healthcare
Adaptation of deep learning to biotechnology/life science industry
PFNでは深層学習を用いて、オミックス解析・医用画像解析・創薬を中心とした研究開発と事業化を行っています。例えば以下の様な研究を行っています
オミックス解析：miRNAを用いたがん診断
医用画像解析：X線・CT・MRI画像を用いた疾患判定
創薬：標的タンパクに結合する化合物のスクリーニング
他にも様々なテーマの研究を進めており、各技術の医療・ライフサイエンス分野への応用を目指します
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
The Second Workshop on GenAI for Health @ NeurIPS2025
By : Wataru Kawakami, Keita Suzuki, Junichiro Iwasawa,
