Impact of Respiratory Bacterial Infections on Mortality in Japanese Patients with COVID-19: a Retrospective Cohort Study.
BMC pulmonary medicine(2023)SCI 3区
Keio University School of Medicine | Tokyo Medical and Dental University Hospital of Medicine | Fukuoka University Hospital | Fukuoka University | Juntendo University | Fukujuji Hospital | Tosei General Hospital | JCHO (Japan Community Health Care Organization | Kumamoto Medical Center | Tokyo Women’s Medical University Adachi Medical Center | Social Welfare Organization Saiseikai Imperial Gift Foundation | National Hospital Organization Tokyo Medical Center | Uji-Tokushukai Medical Center | National Hospital Organization Kyushu Medical Center | National Hospital Organization Hokkaido Medical Center | Ishikawa Prefectural Central Hospital | Osaka University Graduate School of Medicine | Nagoya University Graduate School of Medicine | Gifu University Graduate School of Medicine | National Hospital Organization Kanazawa Medical Center | Saiseikai Yokohamashi Nanbu Hospital | St. Marianna University School of Medicine Kawasaki | St. Marianna University School of Medicine | Tohoku University Graduate School of Medicine | Fukushima Medical University | Toyohashi Municipal Hospital | National Hospital Organization Saitama National Hospital | Osaka Saiseikai Nakatsu Hospital | Saitama Cardiovascular and Respiratory Center | Showa University Koto Toyosu Hospital | Kanagawa Cardiovascular and Respiratory Center | Kansai Medical University General Medical Center | Tokyo Medical University Hospital | Tokyo Medical University Ibaraki Medical Center | Ome Municipal General Hospital | Tsukuba Kinen General Hospital | Fujisawa City Hospital | National Defense Medical College | Kyoto Prefectural University of Medicine | Kitasato University | Genome Medical Science Project (Toyama) | the Institute of Medical Science | Tokyo Medical and Dental University | Kyoto University
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

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Acute Neutrophilic Vasculitis (leukocytoclasia) in 36 COVID-19 Autopsy Brains
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