{"doi":"10.1109/mdm.2017.67","title":"Model Regularization of Deep Neural Networks for Robust Clinical Opinions Generation from General Blood Test Results","abstract":null,"journal":"2017 18th IEEE International Conference on Mobile Data Management (MDM)","year":2017,"id":38492,"datarank":0.1378335591564239,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.03386148207243208,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.03386148207243208,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":1,"citers_with_citation_signal":1,"citers_with_endowment":1,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":176803,"name":"Han-Gyu Kim","orcid":null,"position":1,"is_corresponding":false},{"id":176805,"name":"Ho-Jin Choi","orcid":null,"position":2,"is_corresponding":false},{"id":190856,"name":"Youjin Kim","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"18998881","pmcid":null,"openalex_id":"https://openalex.org/W2728804654","authors":[],"funders":[],"total_grants":0,"fwci":0.195,"citation_percentile":0.60855727,"influential_citations":0,"citation_trend":[{"year":2020,"count":1}],"oa_status":"closed","license":null,"oa_locations":[{"url":"http://xplorestaging.ieee.org/ielx7/7960738/7962417/07962485.pdf?arnumber=7962485","host_type":"publisher"},{"url":"https://doi.org/10.1109/mdm.2017.67","host_type":""}],"fields_of_study":["Machine Learning in Healthcare","Topic Modeling","Imbalanced Data Classification Techniques","Computer Science","Medicine"],"mesh_terms":[],"keywords":["Overfitting","Dropout (neural networks)","Normalization (sociology)","Artificial intelligence","Computer science","Deep neural networks","Regularization (linguistics)","Artificial neural network","Machine learning","Test data","Pattern recognition (psychology)"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-06-11T03:51:43.533177Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}