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臺灣學術機構典藏系統 (Taiwan Academic Institutional Repository, TAIR)
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Institution Date Title Author
臺大學術典藏 2021-07-15T05:32:05Z Using machine learning to improve the discriminative power of the FERD screener in classifying patients with schizophrenia and healthy adults Lee, Shih Chieh; Chen, Kuan Wei; CHEN-CHUNG LIU; Kuo, Chian Jue; I-PING HSUEH; CHING-LIN HSIEH
臺大學術典藏 2021-08-13T03:35:00Z Using machine learning to improve the discriminative power of the FERD screener in classifying patients with schizophrenia and healthy adults Lee S.-C.; Chen K.-W.; CHEN-CHUNG LIU; Kuo C.-J.; Hsueh I.-P.; Hsieh C.-L.
臺大學術典藏 2022-02-10T08:29:44Z Using machine learning to improve the discriminative power of the FERD screener in classifying patients with schizophrenia and healthy adults Lee S.-C.; Chen K.-W.; Liu C.-C.; Kuo C.-J.; Hsueh I.-P.; CHING-LIN HSIEH
臺大學術典藏 2022-02-10T08:29:43Z Using machine learning to improve the discriminative power of the FERD screener in classifying patients with schizophrenia and healthy adults Lee S.-C.; Chen K.-W.; Liu C.-C.; Kuo C.-J.; I-PING HSUEH; Hsieh C.-L.
國立成功大學 2021 Using machine learning to improve the discriminative power of the FERD screener in classifying patients with schizophrenia and healthy adults Lee, S.-C.;Chen, K.-W.;Liu, C.-C.;Kuo, C.-J.;Hsueh, I.-P.;Hsieh, C.-L.
國立成功大學 2024-11 Using machine learning to predict bacteremia in urgent care patients on the basis of triage data and laboratory results Chiu;Chung-Ping;Chou;Hsin-Hung;Lin;Peng-Chan;Lee;Ching-Chi;Hsieh;Sun-Yuan
臺北醫學大學 2014-06-20 Using machine learning to Predict Correlation of Pre-mammography Questionnaire with Breast Cancer 武暁萍; Wu, Hsiao-Ping
國立成功大學 2021-06 Using Machine Learning to Predict Indoor Acoustic Indicators of Multi-Functional Activity Centers Yeh;Chiu-Yu;Tsay;Yaw-Shyan
臺大學術典藏 2021-06-22T02:00:36Z Using machine learning to understand the implications of meteorological conditions for fish kills Chen, Y.-J.;Nicholson, E.;Cheng, S.-T.; Chen, Y.-J.; Nicholson, E.; Cheng, S.-T.; SU-TING CHENG
臺大學術典藏 2022-03-16T01:32:10Z Using Machine Theory of Mind to Learn Agent Social Network Structures from Observed Interactive Behaviors with Targets Chuang Y.-S.; Hung H.-Y.; Gamborino E.; JOSHUA GOH; Huang T.-R.; Chang Y.-L.; Yeh S.-L.; Fu L.-C.

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