Predicting coronavirus disease 2019 severity using explainable artificial intelligence techniques.
Saved in:
| Title: | Predicting coronavirus disease 2019 severity using explainable artificial intelligence techniques. |
|---|---|
| Authors: | Ozawa T; Division of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan., Chubachi S; Division of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan. bachibachi472000@z6.keio.jp., Namkoong H; Department of Infectious Diseases, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan. hounamugun@gmail.com., Nemoto S; Industrial and Digital Business Unit, Hitachi, Ltd, Tokyo, Japan., Ikegami R; Industrial and Digital Business Unit, Hitachi, Ltd, Tokyo, Japan., Asakura T; Division of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan.; Department of Clinical Medicine (Laboratory of Bioregulatory Medicine), Kitasato University School of Pharmacy, Tokyo, Japan.; Department of Respiratory Medicine, Kitasato University, Kitasato Institute Hospital, Tokyo, Japan., Tanaka H; Division of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan., Lee H; Division of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan., Fukushima T; Division of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan., Azekawa S; Division of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan., Otake S; Division of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan., Nakagawara K; Division of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan., Watase M; Division of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan., Masaki K; Division of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan., Kamata H; Division of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan., Harada N; Department of Respiratory Medicine, Faculty of Medicine, Graduate School of Medicine, Juntendo University, Tokyo, Japan., Ueda T; Department of Respiratory Medicine, Osaka Saiseikai Nakatsu Hospital, Osaka, Japan., Ueda S; JCHO (Japan Community Health Care Organization, Internal Medicine, Saitama Medical Center, Saitama, Japan., Ishiguro T; Department of Respiratory Medicine, Saitama Cardiovascular and Respiratory Center, Saitama, Japan., Arimura K; Department of Respiratory Medicine, Tokyo Women's Medical University, Tokyo, Japan., Saito F; Department of Emergency and Critical Care Medicine, Kansai Medical University General Medical Center, Osaka, Japan., Yoshiyama T; Respiratory Disease Center, Fukujuji Hospital, Tokyo, Japan., Nakano Y; Department of Internal Medicine, Kawasaki Municipal Ida Hospital, Kawasaki, Kanagawa, Japan., Muto Y; Department of Infectious Diseases, Tosei General Hospital, Aichi, Japan., Suzuki Y; Department of Clinical Medicine (Laboratory of Bioregulatory Medicine), Kitasato University School of Pharmacy, Tokyo, Japan.; Department of Respiratory Medicine, Kitasato University, Kitasato Institute Hospital, Tokyo, Japan., Edahiro R; Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan., Murakami K; Department of Respiratory Medicine, Tohoku University Graduate School of Medicine, Miyagi, Japan., Sato Y; Biostatistics Unit, Clinical and Translational Research Center, Keio University Hospital, Tokyo, Japan., Okada Y; Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan.; Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan.; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan., Koike R; Health Science Research and Development Center, Tokyo Medical and Dental University, Tokyo, Japan., Ishii M; Division of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan.; Department of Respiratory Medicine, Nagoya University Graduate School of Medicine, Aichi, Japan., Hasegawa N; Department of Infectious Diseases, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan., Kitagawa Y; Department of Surgery, Keio University School of Medicine, Tokyo, Japan., Tokunaga K; Genome Medical Science Project (Toyama), National Center for Global Health and Medicine, Tokyo, Japan., Kimura A; Institute of Research, Tokyo Medical and Dental University, Tokyo, Japan., Miyano S; M&D Data Science Center, Tokyo Medical and Dental University, Tokyo, Japan., Ogawa S; Department of Pathology and Tumor Biology, Kyoto University, Kyoto, Japan.; Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan., Kanai T; Division of Gastroenterology and Hepatology, Department of Medicine, Keio University School of Medicine, Tokyo, Japan., Fukunaga K; Division of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan., Imoto S; Division of Health Medical Intelligence, Human Genome Center, the Institute of Medical Science, the University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-0071, Japan. imoto@hgc.jp. |
| Source: | Scientific reports [Sci Rep] 2025 Mar 19; Vol. 15 (1), pp. 9459. Date of Electronic Publication: 2025 Mar 19. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
| ISSN: | 2045-2322 |
|---|---|
| DOI: | 10.1038/s41598-025-85733-5 |
