D3 Maさんの論文がAmerican Journal of Cardiologyに掲載されました！
Xiaozhi Ma , Yusaku Shibata MD, PhD, Osamu Kurihara MD, PhD , Nobuaki Kobayashi MD, PhD,Masamichi Takano MD, PhD , Toru Kurihara PhD
“Identifying Pathogenesis of Acute Coronary Syndromes using Sequence Contrastive Learning in Coronary Angiograph.”
American Journal of Cardiology, 2025.
https://www.ajconline.org/article/S0002-9149(25)00516-8/fulltext
https://doi.org/10.1016/j.amjcard.2025.08.051
急性冠症候群の２つの病態プラーク破裂（PR)とプラークびらん(PE)を識別しようという試みです。
ニューラルネットワークの学習法を工夫することで正解率があがるというもので、動画像に着目したSequence Contrastive Learning(SeqCon)を提案するものです。将来は、個別化診療につながる新しい可能性を示したもので、まだやれることは山ほどありそうなので、これからもこの研究を精力的に進めていきます。
Maさんのコメント：
We are pleased to share that our paper, ‘Identifying Pathogenesis of Acute Coronary Syndromes using Sequence Contrastive Learning in Coronary Angiography’, has been accepted by the American Journal of Cardiology.
We are so grateful to have achieved this. It means that the reviewers and editors have recognized the value of our proposed algorithm in contributing to medical research on heart coronary disease-Acute Coronary Syndrome (ACS). Previous research work mainly focuses on identifying ACS in Optical Coherence Tomography (OCT) images using deep neural networks.
In contrast, our work aims to identify ACS in X-ray Coronary Angiography (CAG) images, which is a much more challenging task. To achieve effective performance in ACS classification, we proposed an interesting method, Sequence Contrastive Learning (SeqCon), designed to enhance the feature representations.
We take the lead in this area; our paper is the first one to investigate the classification of ACS solely using X-ray images with deep neural networks.
Medical image analysis is an interdisciplinary research bridging engineering and medicine. The success of our accepted paper benefits from strong cooperation. We are especially thankful to the doctors who assisted and helped us, particularly Dr. Osamu Kurihara, for supporting the datasets and providing guidance on formal writing.
The period from drafting and revising to submission has been full of valuable gains in skills, knowledge, and self-improvement. I have learned a lot from Prof. KURIHARA Toru. I think that my writing and experiment design made some trouble for Prof. KURIHARA at the beginning of this research, due to my initial lack of knowledge on how to conduct meaningful and rigorous research, and how to write formal journal papers. Prof. KURIHARA is respected and genuinely knowledgeable scholar. Although he is strict, he has helped me a lot by guiding and correcting me.
I am deeply grateful to Prof. KURIHARA, he guides and led me into the genuine academic research world. In deep and vast research world, I will keep on self-improvement to pursue a better researcher.
