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Federated learning for predicting clinical outcomes in patients with COVID-19.
Dayan I, Roth HR, Zhong A, Harouni A, Gentili A, Abidin AZ, Liu A, Costa AB, Wood BJ, Tsai CS, Wang CH, Hsu CN, Lee CK, Ruan P, Xu D, Wu D, Huang E, Kitamura FC, Lacey G, de Antônio Corradi GC, Nino G, Shin HH, Obinata H, Ren H, Crane JC, Tetreault J, Guan J, Garrett JW, Kaggie JD, Park JG, Dreyer K, Juluru K, Kersten K, Rockenbach MABC, Linguraru MG, Haider MA, AbdelMaseeh M, Rieke N, Damasceno PF, E Silva PMC, Wang P, Xu S, Kawano S, Sriswasdi S, Park SY, Grist TM, Buch V, Jantarabenjakul W, Wang W, Tak WY, Li X, Lin X, Kwon YJ, Quraini A, Feng A, Priest AN, Turkbey B, Glicksberg B, Bizzo B, Kim BS, Tor-Díez C, Lee CC, Hsu CJ, Lin C, Lai CL, Hess CP, Compas C, Bhatia D, Oermann EK, Leibovitz E, Sasaki H, Mori H, Yang I, Sohn JH, Murthy KNK, Fu LC, de Mendonça MRF, Fralick M, Kang MK, Adil M, Gangai N, Vateekul P, Elnajjar P, Hickman S, Majumdar S, McLeod SL, Reed S, Gräf S, Harmon S, Kodama T, Puthanakit T, Mazzulli T, de Lavor VL, Rakvongthai Y, Lee YR, Wen Y, Gilbert FJ, Flores MG, Li Q. Dayan I, et al. Among authors: sriswasdi s. Nat Med. 2021 Oct;27(10):1735-1743. doi: 10.1038/s41591-021-01506-3. Epub 2021 Sep 15. Nat Med. 2021. PMID: 34526699 Free PMC article.
Federated Learning used for predicting outcomes in SARS-COV-2 patients.
Flores M, Dayan I, Roth H, Zhong A, Harouni A, Gentili A, Abidin A, Liu A, Costa A, Wood B, Tsai CS, Wang CH, Hsu CN, Lee CK, Ruan C, Xu D, Wu D, Huang E, Kitamura F, Lacey G, César de Antônio Corradi G, Shin HH, Obinata H, Ren H, Crane J, Tetreault J, Guan J, Garrett J, Park JG, Dreyer K, Juluru K, Kersten K, Bezerra Cavalcanti Rockenbach MA, Linguraru M, Haider M, AbdelMaseeh M, Rieke N, Damasceno P, Cruz E Silva PM, Wang P, Xu S, Kawano S, Sriswasdi S, Park SY, Grist T, Buch V, Jantarabenjakul W, Wang W, Tak WY, Li X, Lin X, Kwon F, Gilbert F, Kaggie J, Li Q, Quraini A, Feng A, Priest A, Turkbey B, Glicksberg B, Bizzo B, Kim BS, Tor-Diez C, Lee CC, Hsu CJ, Lin C, Lai CL, Hess C, Compas C, Bhatia D, Oermann E, Leibovitz E, Sasaki H, Mori H, Yang I, Sohn JH, Keshava Murthy KN, Fu LC, Furtado de Mendonça MR, Fralick M, Kang MK, Adil M, Gangai N, Vateekul P, Elnajjar P, Hickman S, Majumdar S, McLeod S, Reed S, Graf S, Harmon S, Kodama T, Puthanakit T, Mazzulli T, de Lima Lavor V, Rakvongthai Y, Lee YR, Wen Y. Flores M, et al. Among authors: sriswasdi s. Res Sq [Preprint]. 2021 Jan 8:rs.3.rs-126892. doi: 10.21203/rs.3.rs-126892/v1. Res Sq. 2021. PMID: 33442676 Free PMC article. Updated. Preprint.
Multimodality radiomics for tumor prognosis in nasopharyngeal carcinoma.
Khongwirotphan S, Oonsiri S, Kitpanit S, Prayongrat A, Kannarunimit D, Chakkabat C, Lertbutsayanukul C, Sriswasdi S, Rakvongthai Y. Khongwirotphan S, et al. Among authors: sriswasdi s. PLoS One. 2024 Feb 12;19(2):e0298111. doi: 10.1371/journal.pone.0298111. eCollection 2024. PLoS One. 2024. PMID: 38346058 Free PMC article.
Characteristics of Mild Cognitive Impairment Using the Thai Version of the Consortium to Establish a Registry for Alzheimer's Disease Tests: A Multivariate and Machine Learning Study.
Tunvirachaisakul C, Supasitthumrong T, Tangwongchai S, Hemrunroj S, Chuchuen P, Tawankanjanachot I, Likitchareon Y, Phanthumchinda K, Sriswasdi S, Maes M. Tunvirachaisakul C, et al. Among authors: sriswasdi s. Dement Geriatr Cogn Disord. 2018;45(1-2):38-48. doi: 10.1159/000487232. Epub 2018 Apr 4. Dement Geriatr Cogn Disord. 2018. PMID: 29617684
An explainable self-attention deep neural network for detecting mild cognitive impairment using multi-input digital drawing tasks.
Ruengchaijatuporn N, Chatnuntawech I, Teerapittayanon S, Sriswasdi S, Itthipuripat S, Hemrungrojn S, Bunyabukkana P, Petchlorlian A, Chunamchai S, Chotibut T, Chunharas C. Ruengchaijatuporn N, et al. Among authors: sriswasdi s. Alzheimers Res Ther. 2022 Aug 9;14(1):111. doi: 10.1186/s13195-022-01043-2. Alzheimers Res Ther. 2022. PMID: 35945568 Free PMC article.
High Transmission Rates of Early Omicron Subvariant BA.2 in Bangkok, Thailand.
Petcharat S, Supataragul A, Hirunpatrawong P, Torvorapanit P, Klungthong C, Chinnawirotpisan P, Ninwattana S, Thippamom N, Paitoonpong L, Suwanpimolkul G, Jantarabenjakul W, Buathong R, Joonlasak K, Manasatienkij W, Rattanatumhi K, Chantasrisawad N, Chumpa N, Cotrone TS, Fernandez S, Sriswasdi S, Wacharapluesadee S, Putcharoen O. Petcharat S, et al. Among authors: sriswasdi s. Adv Virol. 2023 Dec 6;2023:4940767. doi: 10.1155/2023/4940767. eCollection 2023. Adv Virol. 2023. PMID: 38094619 Free PMC article.
Correction: Machine learning-based normal tissue complication probability model for predicting albumin-bilirubin (ALBI) grade increase in hepatocellular carcinoma patients.
Prayongrat A, Srimaneekarn N, Thonglert K, Khorprasert C, Amornwichet N, Alisanant P, Shirato H, Kobashi K, Sriswasdi S. Prayongrat A, et al. Among authors: sriswasdi s. Radiat Oncol. 2023 Mar 15;18(1):53. doi: 10.1186/s13014-023-02212-9. Radiat Oncol. 2023. PMID: 36922889 Free PMC article. No abstract available.
66 results