Browsing by Keyword : machine learning
Showing results 24 to 35 of 35
Pub Year | | Title | AJOU Author(s) |
2018 | | PIP-EL: A New Ensemble Learning Method for Improved Proinflammatory Peptide Predictions | Balachandran, Manavalan, 이광 |
2024 | | Predicting the Outcome of Pediatric Oral Food Challenges for Determining Tolerance Development | 정경욱 |
2022 | | Prediction Model for 30-Day Mortality after Non-Cardiac Surgery Using Machine-Learning Techniques Based on Preoperative Evaluation of Electronic Medical Records | 김하연, 박래웅 |
2023 | | Prediction model for postoperative atrial fibrillation in non-cardiac surgery using machine learning | 김하연 |
2024 | | Prediction Models for Readmission Using Home Healthcare Notes and OMOP-CDM | 박래웅 |
2020 | | Prediction of Major Depressive Disorder Following Beta-Blocker Therapy in Patients with Cardiovascular Diseases | 박래웅, 손상준, 진우람 |
2018 | | PVP-SVM: Sequence-Based Prediction of Phage Virion Proteins Using a Support Vector Machine | Balachandran, Manavalan, 이광 |
2019 | | SDM6A: A Web-Based Integrative Machine-Learning Framework for Predicting 6mA Sites in the Rice Genome | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광 |
2021 | | StackIL6: a stacking ensemble model for improving the prediction of IL-6 inducing peptides | Balachandran, Manavalan |
2022 | | STALLION: A stacking-based ensemble learning framework for prokaryotic lysine acetylation site prediction | Balachandran, Manavalan, Basith, Shaherin, 이광 |
2022 | | THRONE: A New Approach for Accurate Prediction of Human RNA N7-Methylguanosine Sites | Basith, Shaherin, 이광 |
2024 | | Towards global model generalizability: independent cross-site feature evaluation for patient-level risk prediction models using the OHDSI network | 박래웅 |
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