Deep learning-based age estimation from chest X-rays indicates cardiovascular prognosis

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作者
Hirotaka Ieki
Kaoru Ito
Mike Saji
Rei Kawakami
Yuji Nagatomo
Kaori Takada
Toshiya Kariyasu
Haruhiko Machida
Satoshi Koyama
Hiroki Yoshida
Ryo Kurosawa
Hiroshi Matsunaga
Kazuo Miyazawa
Kouichi Ozaki
Yoshihiro Onouchi
Susumu Katsushika
Ryo Matsuoka
Hiroki Shinohara
Toshihiro Yamaguchi
Satoshi Kodera
Yasutomi Higashikuni
Katsuhito Fujiu
Hiroshi Akazawa
Nobuo Iguchi
Mitsuaki Isobe
Tsutomu Yoshikawa
Issei Komuro
机构
[1] RIKEN Center for Integrative Medical Sciences,Laboratory for Cardiovascular Genomics and Informatics
[2] The University of Tokyo,Department of Cardiovascular Medicine, Graduate School of Medicine
[3] Sakakibara Heart Institute,Department of Cardiology
[4] Tokyo Institute of Technology,Department of Computer Science, School of Computing
[5] National Defense Medical College,Department of Cardiology
[6] Sakakibara Heart Institute,Department of Radiology
[7] Tokyo Women’s Medical University,Department of Radiology
[8] Medical Center East,Division for Genomic Medicine, Medical Genome Center
[9] National Center for Geriatrics and Gerontology,Department of Public Health
[10] Chiba University Graduate School of Medicine,Center for Epidemiology and Preventive Medicine
[11] The University of Tokyo Hospital,undefined
[12] Sakakibara Heart Institute,undefined
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摘要
Chest X-ray is one of the most widely used medical imaging tests worldwide to diagnose and manage heart and lung diseases. In this study, we developed a computer-based tool to predict patients’ age from chest X-rays. The tool precisely estimated patients’ age from chest X-rays. Furthermore, in patients with heart failure and those admitted to the intensive care unit for cardiovascular disease, elevated X-ray age estimated by our tool was associated with poor clinical outcomes, including readmission for heart failure or death from any cause. With further testing, our tool may help clinicians to predict outcomes in patients with heart disease based on a simple chest X-ray.
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