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Deep-learning-based personalized prediction of absolute neutrophil count recovery and comparison with clinicians for validation.
Choo, Hyunwoo; Yoo, Su Young; Moon, Suhyeon; Park, Minsu; Lee, Jiwon; Sung, Ki Woong; Cha, Won Chul; Shin, Soo-Yong; Son, Meong Hi.
Affiliation
  • Choo H; Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea; Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Seoul, Republic of Korea.
  • Yoo SY; Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea.
  • Moon S; Research Institute for Future Medicine, Samsung Medical Center, Seoul, Republic of Korea.
  • Park M; Department of Information and Statistics, Chungnam National University, Korea 99 Daehak-ro, Yuseong-gu, Daejeon, Republic of Korea.
  • Lee J; Department of Pediatrics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Sung KW; Department of Pediatrics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Cha WC; Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Shin SY; Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea; Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Seoul, Republic of Korea; Research Institute for Future Medicine, Samsung Medical Center, Seoul, Republic of Korea. Electronic
  • Son MH; Department of Pediatrics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. Electronic address: meonghi.son@samsung.com.
J Biomed Inform ; 137: 104268, 2023 01.
Article in En | MEDLINE | ID: mdl-36513332
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Deep Learning / Neoplasms / Neutropenia Type of study: Prognostic_studies / Risk_factors_studies Limits: Child / Humans Language: En Journal: J Biomed Inform Journal subject: INFORMATICA MEDICA Year: 2023 Document type: Article Country of publication:
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Deep Learning / Neoplasms / Neutropenia Type of study: Prognostic_studies / Risk_factors_studies Limits: Child / Humans Language: En Journal: J Biomed Inform Journal subject: INFORMATICA MEDICA Year: 2023 Document type: Article Country of publication: