Tottori University

Usefulness of deep learning-assisted identification of hyperdense MCA sign in acute ischemic stroke: comparison with readers’ performance

Yuki Shinohara, Noriyuki Takahashi, Yongbum Lee et al.

2020 · 14 Zit.

Emulating Visual Evaluations in the Microscopic Agglutination Test with Deep Learning

Risa Nakano, Yuji Oyamada, Ryo Ozuru et al.

2024 · 2 Zit.

IFCN position statement: use of artificial intelligence in clinical neurophysiology

Aatif M. Husain, Sandor Beniczky, Meriem Bensalem-Owen et al.

2026 · 1 Zit.

Examining the Effect of ChatGPT on Small Group Ideation Discussions

Madoka Chosokabe, Shohei Koie, Yuji Oyamada

2024 · 1 Zit.

Comparative Analysis of Machine Learning for Stroke Classification Using YOLOv11 Detection and a Radiomics-Based Two-Stage Model

Wahyu Ozorah Manurung, Ernawati Ernawati, Widhia K.Z. Oktoeberza et al.

2026 · 0 Zit.

日本語教育における生成AI活用研究のスコーピングレビュー

準二 片桐

2026 · 0 Zit.

Characteristics of images from CT scans in elderly patients with acute cardiogenic pulmonary edema

Hirokazu Touge, Katsuyuki Tomita, Masaharu Fukuki et al.

2018 · 0 Zit.

Utilization of Explainable Artificial Intelligence (XAI)-Powered Computer-Aided Detection (CAD) System on Chest X-Ray Abnormalities in Health Check-Ups

Shizuka Nishii, Katsuyuki Tomita, Hirokazu Touge et al.

2025 · 0 Zit.

Expanding L2 Vocabulary Learning Opportunities Through ChatGPT and Other AI Chatbots

Christopher HOLLIS

2026 · 0 Zit.