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Showing results 1 to 13 of 13

Publication Date2021-06-01 A comprehensive assessment of empirical potentials for carbon materials
Cheng Qian; Ben McLean; Daniel Hedman, et al
APL Materials, v.9, no.6
Publication Date2023-04 A machine learning approach to discover migration modes and transition dynamics of heterogeneous dendritic cells
Song, T.; Yongjun Choi; Jeon, J.-H., et al
Frontiers in Immunology, v.14
Publication Date2023-03 Closed-loop optimization of nanoparticle synthesis enabled by robotics and machine learning
Jungwon Park; Kim, Y.M.; Hong, S., et al
Matter, v.6, no.3, pp.677 - 690
Publication Date2024-01 Combined radiomics-clinical model to predict platinum-sensitivity in advanced high-grade serous ovarian carcinoma using multimodal MRI
Na, Inye; Noh, Joseph J.; Kim, Chan Kyo, et al
Frontiers in Oncology, v.14
Publication Date2022-03 Decomposing MRI phenotypic heterogeneity in epilepsy: a step towards personalized classification
Lee, Hyo Min; Fadaie, Fatemeh; Gill, Ravnoor, et al
BRAIN, v.145, no.3, pp.897 - 908
Publication Date2022-10 Disaster assessment using computer vision and satellite imagery: Applications in detecting water-related building damages
Danu Kim; Won, Jeongkyung; Eunji Lee, et al
FRONTIERS IN ENVIRONMENTAL SCIENCE, v.10
Publication Date2023-10 Imputing missing sleep data from wearables with neural networks in real-world settings
Lee, Minki P.; Hoang, Kien; Park, Sungkyu, et al
SLEEP, v.47, no.1
Publication Date2020-11 Investigating Mitonuclear Genetic Interactions Through Machine Learning: A Case Study on Cold Adaptation Genes in Human Populations From Different European Climate Regions
Alena Kalyakulina; Vincenzo Iannuzzi; Marco Sazzini, et al
Frontiers in Physiology, v.11, pp.575968
Publication Date2023-09 Predicting the Risk of Sleep Disorders Using a Machine Learning-Based Simple Questionnaire: Development and Validation Study
Seokmin Ha; Choi, Su Jung; Lee, Sujin, et al
Journal of medical Internet research, v.25, no.1, pp.e46520
Publication Date2020-04 Predicting Trial-by-Trial Variation in Oculomotor Behavior Using Multivariate Electroencephalography Theta Phase
Woojae Jeong; Seolmin Kim; Yee-Joon Kim, et al
IEEE Access, v.8, pp.65544 - 65553
Publication Date2019-03 Prediction of major regio-, site-, and diastereoisomers in Diels-Alder reactions using machine-learning: The importance of physically meaningful descriptors
Wiktor Beker; Ewa Gajewska; Tomasz Badowski, et al
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION, v.58, no.14, pp.4515 - 4519
Publication Date2020-12 Whole-brain functional connectivity correlates of obesity phenotypes
Bo-yong Park; Kyoungseob Byeon; Mi Ji Lee, et al
HUMAN BRAIN MAPPING, v.41, no.17, pp.4912 - 4924
Publication Date2023-04 Whole-brain functional gradients reveal cortical and subcortical alterations in patients with episodic migraine
Lee, Chae Hyeon; Hyunjin Park; Lee, Mi Ji, et al
HUMAN BRAIN MAPPING, v.44, no.6, pp.2224 - 2233

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