Browsing by Keyword : Machine Learning
Showing results 49 to 59 of 59
| Pub Year | | Title | AJOU Author(s) |
| 2021 | | Predicting speech discrimination scores from pure-tone thresholds—A machine learning-based approach using data from 12,697 subjects | 김한태, 장정훈, 정연훈 |
| 2019 | | Prediction of cognitive impairment via deep learning trained with multi-center neuropsychological test data | 문소영 |
| 2023 | | Privacy-Preserving Federated Model Predicting Bipolar Transition in Patients With Depression: Prediction Model Development Study | 박래웅, 손상준 |
| 2022 | | Recent Trends on the Development of Machine Learning Approaches for the Prediction of Lysine Acetylation Sites | Basith, Shaherin, 이광, 장혜진 |
| 2024 | | SEP-AlgPro: An efficient allergen prediction tool utilizing traditional machine learning and deep learning techniques with protein language model features | Basith, Shaherin, 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 | | The Bio-signal based Model to Predict the Occurrence of Delirium in Intensive Care Unit(ICU) | 김형준 |
| 2022 | | THRONE: A New Approach for Accurate Prediction of Human RNA N7-Methylguanosine Sites | Basith, Shaherin, 이광 |
| 2023 | | Translation of Machine Learning-Based Prediction Algorithms to Personalised Empiric Antibiotic Selection: A Population-Based Cohort Study | 박래웅, 최영화 |
| 2021 | | Umpred-frl: A new approach for accurate prediction of umami peptides using feature representation learning | Balachandran, Manavalan |
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