1. A deep learning system to diagnose the malignant potential of urothelial carcinoma cells in cytology specimens. Issue 12 (12th May 2021) Authors: Nojima, Satoshi; Terayama, Kei; Shimoura, Saeko; Hijiki, Sachiko; Nonomura, Norio; Morii, Eiichi; Okuno, Yasushi; Fujita, Kazutoshi Journal: Cancer cytopathology Issue: Volume 129:Issue 12(2021) Page Start: 984 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
2. A machine learning–based classification approach for phase diagram prediction. (March 2022) Authors: Deffrennes, Guillaume; Terayama, Kei; Abe, Taichi; Tamura, Ryo Journal: Materials & design Issue: Volume 215(2022) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
3. Acceleration of phase diagram construction by machine learning incorporating Gibbs' phase rule. (1st February 2022) Authors: Terayama, Kei; Han, Kwangsik; Katsube, Ryoji; Ohnuma, Ikuo; Abe, Taichi; Nose, Yoshitaro; Tamura, Ryo Journal: Scripta materialia Issue: Number 208(2022) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
4. Automatic Rietveld refinement by robotic process automation with RIETAN-FP. Issue 1 (31st December 2022) Authors: Tamura, Ryo; Sumita, Masato; Terayama, Kei; Tsuda, Koji; Izumi, Fujio; Matsushita, Yoshitaka Journal: Science and Technology of Advanced Materials: Methods Issue: Volume 2:Issue 1(2022) Page Start: 435 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
5. ChemTS: an efficient python library for de novo molecular generation. Issue 1 (31st December 2017) Authors: Yang, Xiufeng; Zhang, Jinzhe; Yoshizoe, Kazuki; Terayama, Kei; Tsuda, Koji Journal: Science and technology of advanced materials Issue: Volume 18:Issue 1(2017) Page Start: 972 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
6. Computer Vision-Based Approach for Quantifying Occupational Therapists' Qualitative Evaluations of Postural Control. (27th April 2020) Authors: Hagihara, Hiromichi; Ienaga, Naoto; Enomoto, Daiki; Takahata, Shuhei; Ishihara, Hiroyuki; Noda, Haruka; Tsuda, Koji; Terayama, Kei Other Names: Hilton Claudia Academic Editor. Journal: Occupational therapy international Issue: Volume 2020(2020) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
7. Cost‐effective seafloor habitat mapping using a portable speedy sea scanner and deep‐learning‐based segmentation: A sea trial at Pujada Bay, Philippines. Issue 2 (30th October 2021) Authors: Terayama, Kei; Mizuno, Katsunori; Tabeta, Shigeru; Sakamoto, Shingo; Sugimoto, Yusuke; Sugimoto, Kenichi; Fukami, Hironobu; Sakagami, Masaaki; Jimenez, Lea A. Journal: Methods in ecology and evolution Issue: Volume 13:Issue 2(2022) Page Start: 339 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
8. CrySPY: a crystal structure prediction tool accelerated by machine learning. Issue 1 (1st January 2021) Authors: Yamashita, Tomoki; Kanehira, Shinichi; Sato, Nobuya; Kino, Hiori; Terayama, Kei; Sawahata, Hikaru; Sato, Takumi; Utsuno, Futoshi; Tsuda, Koji; Miyake, Takashi; Oguchi, Tamio Journal: Science and Technology of Advanced Materials: Methods Issue: Volume 1:Issue 1(2021) Page Start: 87 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
9. Development and Verification of Postural Control Assessment Using Deep-Learning-Based Pose Estimators: Towards Clinical Applications. (30th November 2022) Authors: Ienaga, Naoto; Takahata, Shuhei; Terayama, Kei; Enomoto, Daiki; Ishihara, Hiroyuki; Noda, Haruka; Hagihara, Hiromichi Other Names: Bin Sheng Academic Editor. Journal: Occupational therapy international Issue: Volume 2022(2022) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
10. Improving the Accuracy of Protein‐Ligand Binding Mode Prediction Using a Molecular Dynamics‐Based Pocket Generation Approach. Issue 32 (4th December 2018) Authors: Araki, Mitsugu; Iwata, Hiroaki; Ma, Biao; Fujita, Atsuto; Terayama, Kei; Sagae, Yukari; Ono, Fumie; Tsuda, Koji; Kamiya, Narutoshi; Okuno, Yasushi Journal: Journal of computational chemistry Issue: Volume 39:Issue 32(2018) Page Start: 2679 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗