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Herdiantri Sufriyana

Showing results (1-10 of 19) with videos related to

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Studies in Health Technology and Informatics|August 8, 2025
Development of Rmlnomogram: An R Package to Construct an Explainable Nomogram for Any Machine Learning AlgorithmsHerdiantri Sufriyana, Emily Chia-Yu Su
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 3, 2025
Development of rplec: An R package of placental epigenetic clock to estimate aging by DNA-methylation-based gestational ageHerdiantri Sufriyana, Emily Chia-Yu Su
Ebiomedicine|April 14, 2020
Artificial intelligence-assisted prediction of preeclampsia: Development and external validation of a nationwide health insurance dataset of the BPJS Kesehatan in IndonesiaHerdiantri Sufriyana, Yu-Wei Wu, Emily Chia-Yu Su
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|December 31, 2023
Low- and high-level information analyses of transcriptome connecting endometrial-decidua-placental origin of preeclampsia subtypes: A preliminary studyHerdiantri Sufriyana, Yu-Wei Wu, Emily Chia-Yu Su
Plos One|January 25, 2023
Questionnaire-free machine-learning method to predict depressive symptoms among community-dwelling older adultsSri Susanty, Herdiantri Sufriyana, Emily Chia-Yu Su, et al.
Neural Networks : the Official Journal of the International Neural Network Society|March 10, 2023
Human-guided deep learning with ante-hoc explainability by convolutional network from non-image data for pregnancy prognosticationHerdiantri Sufriyana, Yu-Wei Wu, Emily Chia-Yu Su
JMIR Medical Informatics|April 30, 2020
Prediction of Preeclampsia and Intrauterine Growth Restriction: Development of Machine Learning Models on a Prospective CohortHerdiantri Sufriyana, Yu-Wei Wu, Emily Chia-Yu Su
Computational and Structural Biotechnology Journal|August 15, 2022
Blood biomarkers representing maternal-fetal interface tissues used to predict early-and late-onset preeclampsia but not COVID-19 infectionHerdiantri Sufriyana, Hotimah Masdan Salim, Akbar Reza Muhammad, et al.
Scientific Reports|March 11, 2025
Widely accessible prognostication using medical history for fetal growth restriction and small for gestational age in nationwide insured womenHerdiantri Sufriyana, Fariska Zata Amani, Aufar Zimamuz Zaman Al Hajiri, et al.
Studies in Health Technology and Informatics|January 25, 2024
Prognosticating Fetal Growth Restriction and Small for Gestational Age by Medical HistoryHerdiantri Sufriyana, Fariska Zata Amani, Aufar Zimamuz Zaman Al Hajiri, et al.
Pageof 2

Showing results (1-10 of 19) with videos related to

Sort By:
Pageof 2
Studies in Health Technology and Informatics|August 8, 2025
Development of Rmlnomogram: An R Package to Construct an Explainable Nomogram for Any Machine Learning AlgorithmsHerdiantri Sufriyana, Emily Chia-Yu Su
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 3, 2025
Development of rplec: An R package of placental epigenetic clock to estimate aging by DNA-methylation-based gestational ageHerdiantri Sufriyana, Emily Chia-Yu Su
Ebiomedicine|April 14, 2020
Artificial intelligence-assisted prediction of preeclampsia: Development and external validation of a nationwide health insurance dataset of the BPJS Kesehatan in IndonesiaHerdiantri Sufriyana, Yu-Wei Wu, Emily Chia-Yu Su
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|December 31, 2023
Low- and high-level information analyses of transcriptome connecting endometrial-decidua-placental origin of preeclampsia subtypes: A preliminary studyHerdiantri Sufriyana, Yu-Wei Wu, Emily Chia-Yu Su
Plos One|January 25, 2023
Questionnaire-free machine-learning method to predict depressive symptoms among community-dwelling older adultsSri Susanty, Herdiantri Sufriyana, Emily Chia-Yu Su, et al.
Neural Networks : the Official Journal of the International Neural Network Society|March 10, 2023
Human-guided deep learning with ante-hoc explainability by convolutional network from non-image data for pregnancy prognosticationHerdiantri Sufriyana, Yu-Wei Wu, Emily Chia-Yu Su
JMIR Medical Informatics|April 30, 2020
Prediction of Preeclampsia and Intrauterine Growth Restriction: Development of Machine Learning Models on a Prospective CohortHerdiantri Sufriyana, Yu-Wei Wu, Emily Chia-Yu Su
Computational and Structural Biotechnology Journal|August 15, 2022
Blood biomarkers representing maternal-fetal interface tissues used to predict early-and late-onset preeclampsia but not COVID-19 infectionHerdiantri Sufriyana, Hotimah Masdan Salim, Akbar Reza Muhammad, et al.
Scientific Reports|March 11, 2025
Widely accessible prognostication using medical history for fetal growth restriction and small for gestational age in nationwide insured womenHerdiantri Sufriyana, Fariska Zata Amani, Aufar Zimamuz Zaman Al Hajiri, et al.
Studies in Health Technology and Informatics|January 25, 2024
Prognosticating Fetal Growth Restriction and Small for Gestational Age by Medical HistoryHerdiantri Sufriyana, Fariska Zata Amani, Aufar Zimamuz Zaman Al Hajiri, et al.
Pageof 2