Yokohama City University

Artificial Intelligence in Andrology: From Semen Analysis to Image Diagnostics

Ramy Abou Ghayda, Rossella Cannarella, Aldo E. Calogero et al.

2023 · 69 Zit.

Influence on the accuracy in ChatGPT: Differences in the amount of information per medical field

Tatsuya Haze, Rina Kawano, Hajime Takase et al.

2023 · 66 Zit.

Should We Acknowledge ChatGPT as an Author?

Atsushi Goto, Kota Katanoda

2023 · 34 Zit.

An artificial intelligence-based nerve recognition model is useful as surgical support technology and as an educational tool in laparoscopic and robot-assisted rectal cancer surgery

Kazuya Kinoshita, Tetsuro Maruyama, Nao Kobayashi et al.

2024 · 19 Zit.

Comparison of machine-learning and logistic regression models for prediction of 30-day unplanned readmission in electronic health records: A development and validation study

Masao Iwagami, Ryota Inokuchi, Eiryo Kawakami et al.

2024 · 15 Zit.

A Learning Program for Treatment Recommendations by Molecular Tumor Boards and Artificial Intelligence

Kuniko Sunami, Yoichi Naito, Yusuke Saigusa et al.

2023 · 13 Zit.

Performance evaluation of ChatGPT in detecting diagnostic errors and their contributing factors: an analysis of 545 case reports of diagnostic errors

Yukinori Harada, Tomoharu Suzuki, Taku Harada et al.

2024 · 13 Zit.

Performance of Artificial Intelligence Chatbots in Answering Clinical Questions on Japanese Practical Guidelines for Implant-based Breast Reconstruction

Makoto Shiraishi, Yoshihiro Sowa, Koichi Tomita et al.

2024 · 12 Zit.

Generative artificial intelligence model for simulating structural brain changes in schizophrenia

Hiroyuki Yamaguchi, Genichi Sugihara, Masaaki Shimizu et al.

2024 · 5 Zit.

A prospective study comparing highly qualified Molecular Tumor Boards with AI-powered software as a medical device

Hideaki Bando, Yoichi Naito, Tomoyuki Yamada et al.

2024 · 1 Zit.

PICO and Risk Of bias Navigator for Evidence Based Medicine

Tomohide Yamada, Yoshinobu Kondo, Ryo Momosaki

2019 · 1 Zit.

Delineating retinal breaks in ultra-widefield fundus images with a PraNet-based machine learning model

Takuya Takayama, Tsubasa Uto, Taiki Tsuge et al.

2025 · 1 Zit.

Comparing Conventional and Generative AI–Assisted Task Performance in Physiology Education

Kagemichi Nagao, Masanari Umemura, Yu Iida et al.

2026 · 0 Zit.

Artificial Intelligence and Tacit Knowledge Integration in Midwifery: Policy Implications for Improving Healthcare Outcomes

Shoko Takeuchi, Kazumi Kubota, Sachiyo Nakamura

2025 · 0 Zit.

PICO and Risk Of bias Navigator for Evidence Based Medicine

Tomohide Yamada, Yoshinobu Kondo, Ryo Momosaki

2019 · 0 Zit.