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Melancholic Depression Prediction by Identifying Representative Features in Metabolic and Microarray Profiles with Missing Values.

, , , , , , , and . Pacific Symposium on Biocomputing, page 455-466. (2015)

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Predict Risk of Relapse for Patients with Multiple Stages of Treatment of Depression., , and . KDD, page 1795-1804. ACM, (2016)Melancholic Depression Prediction by Identifying Representative Features in Metabolic and Microarray Profiles with Missing Values., , , , , , , and . Pacific Symposium on Biocomputing, page 455-466. (2015)Efficient SPARQL Query Processing in MapReduce through Data Partitioning and Indexing., , , , and . APWeb, volume 7235 of Lecture Notes in Computer Science, page 628-635. Springer, (2012)Pruning Decision Trees via Max-Heap Projection., , , , , and . SDM, page 10-18. SIAM, (2017)Sparse Generalized Functional Linear Model for Predicting Remission Status of Depression Patients., , , , , , and . Pacific Symposium on Biocomputing, page 364-375. (2014)Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2021., , , , , , , , , and 156 other author(s). Nucleic Acids Res., 49 (Database-Issue): D18-D28 (2021)Machine Learning Methods for Diagnosis, Prognosis and Prediction of Long-term Treatment Outcome of Major Depression.. Arizona State University, Tempe, USA, (2017)base-search.net (ftarizonastateun:item:44430).Self-supervised Image-based 3D Model Retrieval., , , , , , and . ACM Trans. Multim. Comput. Commun. Appl., 19 (2): 70:1-70:18 (2023)Monocular Image-Based 3-D Model Retrieval: A Benchmark., , , , and . IEEE Trans. Cybern., 52 (8): 8114-8127 (2022)Universal Cross-Domain 3D Model Retrieval., , , , , and . IEEE Trans. Multim., (2021)