{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/120224"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/120224","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Natural language processing to support evidence quality assessment of clinical literature","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms","abstract_has_math":false,"creators":["Hoang, Khanh Linh"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Library & Information Science","degree_department":null,"school":null,"contributors":["Kilicoglu, Halil","Ludäscher, Bertram","Diesner, Jana","Boyce, Richard D"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-05","date_published":"2023-05","updated_at":"2026-07-22T22:24:57Z","subjects":["Natural Language Processing","Machine Learning","Biomedical","Evidence Quality Assessment"],"languages":["en","eng"],"rights":["N/A"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/120224","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Kilicoglu, Halil","Ludäscher, Bertram","Diesner, Jana","Boyce, Richard D"]},{"key":"dc:creator","label":"Author","values":["Hoang, Khanh Linh"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2023-05","2023-04-03"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Library & Information Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Natural Language Processing","Machine Learning","Biomedical","Evidence Quality Assessment"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["N/A"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/120224"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms","The student, Khanh Linh Hoang, accepted the attached license on 2023-03-27 at 15:55.","The student, Khanh Linh Hoang, submitted this Dissertation for approval on 2023-03-27 at 16:05.","This Dissertation was approved for publication on 2023-04-03 at 16:07.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18897 on 2023-09-01 at 17:07:51","Evidence Synthesis is the process of synthesizing information from clinical literature to translate the research findings into patient care and healthcare policy. Throughout the evidence synthesis process, a critical yet challenging step is the quality assessment of clinical studies. Quality in research can be considered through two aspects: methodological quality which concerns how rigorously a research is designed and conducted, and reporting quality which describes how transparently a piece of scientific work is reported as a publication. This thesis explores natural language processing (NLP) approaches to support evidence quality assessment of clinical studies. Specifically, I consider different levels of information granularity used for evidence assessment, and implemented three machine learning developments: (1) Classification of evidence types from clinical publications based on study designs, (2) Classification of sentences from randomized controlled trials (RCTs) with checklist items recommended in reporting guidelines, (3) Extraction of fine- grained methodological characteristics from RCTs to assist methodological quality assessment. Applications of these NLP approaches range from assisting authors in checking their manuscripts for compliance with reporting guidelines and supporting journal editors and peer reviewers in assessing papers (pre-publication) to assisting systematic reviewers in synthesizing evidence and meta-researchers in studying research rigor and transparency (post-publication)."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Natural language processing to support evidence quality assessment of clinical literature"]}]}],"canonical_facts":{"dc:contributor":["Kilicoglu, Halil","Ludäscher, Bertram","Diesner, Jana","Boyce, Richard D"],"dc:creator":["Hoang, Khanh Linh"],"dc:date":["2023-05","2023-04-03"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. 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This thesis explores natural language processing (NLP) approaches to support evidence quality assessment of clinical studies. Specifically, I consider different levels of information granularity used for evidence assessment, and implemented three machine learning developments: (1) Classification of evidence types from clinical publications based on study designs, (2) Classification of sentences from randomized controlled trials (RCTs) with checklist items recommended in reporting guidelines, (3) Extraction of fine- grained methodological characteristics from RCTs to assist methodological quality assessment. Applications of these NLP approaches range from assisting authors in checking their manuscripts for compliance with reporting guidelines and supporting journal editors and peer reviewers in assessing papers (pre-publication) to assisting systematic reviewers in synthesizing evidence and meta-researchers in studying research rigor and transparency (post-publication)."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/120224"],"dc:language":["en","eng"],"dc:rights":["N/A"],"dc:subject":["Natural Language Processing","Machine Learning","Biomedical","Evidence Quality Assessment"],"dc:title":["Natural language processing to support evidence quality assessment of clinical literature"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Library & Information Science"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:57Z"}