| Comparison of multivariable logistic regression and other machine learning algorithms for prognostic prediction studies in pregnancy care: systematic review and meta-analysis H Sufriyana, A Husnayain, YL Chen, CY Kuo, O Singh, TY Yeh, YW Wu, ... JMIR medical informatics 8 (11), e16503, 2020 | 82 | 2020 |
| Artificial intelligence-assisted prediction of preeclampsia: Development and external validation of a nationwide health insurance dataset of the BPJS Kesehatan in Indonesia H Sufriyana, YW Wu, ECY Su EBiomedicine 54, 102710, 2020 | 58 | 2020 |
| Prediction of preeclampsia and intrauterine growth restriction: development of machine learning models on a prospective cohort H Sufriyana, YW Wu, ECY Su JMIR medical informatics 8 (5), e15411, 2020 | 37 | 2020 |
| Deep learning for abdominal ultrasound: A computer-aided diagnostic system for the severity of fatty liver TH Chou, HJ Yeh, CC Chang, JH Tang, WY Kao, IC Su, CH Li, WH Chang, ... Journal of the Chinese Medical Association 84 (9), 842-850, 2021 | 28 | 2021 |
| Lightweight deep neural networks for cholelithiasis and cholecystitis detection by point-of-care ultrasound CJ Yu, HJ Yeh, CC Chang, JH Tang, WY Kao, WC Chen, YJ Huang, ... Computer Methods and Programs in Biomedicine 211, 106382, 2021 | 13 | 2021 |
| Human and machine learning pipelines for responsible clinical prediction using high-dimensional data H Sufriyana, YW Wu, ECY Su | 5 | 2021 |
| Deep-insight visible neural network (DI-VNN) for improving interpretability of a non-image deep learning model by data-driven ontology H Sufriyana, YW Wu, ECY Su | 5 | 2021 |
| Resampled dimensional reduction for feature representation in machine learning H Sufriyana, YW Wu, ECY Su | 3 | 2023 |
| Systematic human learning by literature and data mining for feature selection in machine learning H Sufriyana, YW Wu, ECY Su | 3 | 2021 |
| Prognostication for prelabor rupture of membranes and the time of delivery in nationwide insured women: development, validation, and deployment H Sufriyana, YW Wu, ECY Su medRxiv, 2021.06. 16.21258884, 2021 | 3 | 2021 |
| Questionnaire-free machine-learning method to predict depressive symptoms among community-dwelling older adults S Susanty, H Sufriyana, ECY Su, YH Chuang PLoS One 18 (1), e0280330, 2023 | 2 | 2023 |
| Blood biomarkers representing maternal-fetal interface tissues used to predict early-and late-onset preeclampsia but not COVID-19 infection H Sufriyana, HM Salim, AR Muhammad, YW Wu, ECY Su Computational and structural biotechnology journal 20, 4206-4224, 2022 | 2 | 2022 |
| Quantifying medical histories with the Kaplan-Meier (KM) estimator for feature extraction of electronic health records in machine learning H Sufriyana, YW Wu, ECY Su | 2 | 2021 |
| Anti-eczema Mechanism of Action of Nigella sativa for Atopic Dermatitis: Computer-aided Prediction and Pathway Analysis Based on Protein-chemical Interaction Networks MS Widyaswari, I Noventi, H Sufriyana Biomolecular and Health Science Journal 2 (2), 68-74, 2019 | 2 | 2019 |
| Human-guided deep learning with ante-hoc explainability by convolutional network from non-image data for pregnancy prognostication H Sufriyana, YW Wu, ECY Su Neural Networks 162, 99-116, 2023 | 1 | 2023 |
| Low-and high-level information analyses of transcriptome connecting endometrial-decidua-placental origin of preeclampsia subtypes: A preliminary study H Sufriyana, YW Wu, ECY Su PACIFIC SYMPOSIUM ON BIOCOMPUTING 2024, 549-563, 2023 | 1 | 2023 |
| Kemampuan Konsentrasi Berhubungan dengan Waktu Reaksi tetapi Tidak Berhubungan dengan Pola Tidur di Pondok Pesantren H Sufriyana, AAA Firdaus Qanun Medika-Medical Journal Faculty of Medicine Muhammadiyah Surabaya 2 (01), 2018 | 1 | 2018 |
| Nomogram for a machine learning model with categorical predictors to predict binary outcome H Sufriyana, ECY Su | | 2024 |
| Estimating individual risk of catheter-associated urinary tract infections using explainable artificial intelligence on clinical data H Sufriyana, C Chen, HS Chiu, P Sumazin, PY Yang, JH Kang, ECY Su medRxiv, 2024.03. 22.24304712, 2024 | | 2024 |
| Widely accessible prognostication using medical history for fetal growth restriction and small for gestational age in nationwide insured women H Sufriyana, FZ Amani, AZZ Al Hajiri, YW Wu, ECY Su medRxiv, 2024.01. 08.24300958, 2024 | | 2024 |
Yu-Wei WuTaipei Medical University在 tmu.edu.tw 的电子邮件经过验证
