BMC Medical Research Methodology最新文献

{"title":"Creating an indexing scheme for case series articles.","authors":"Andrew Shahidehpour, Arthur W Holt, Ang Michael Troy, Joe D Menke, Neil R Smalheiser","doi":"10.1186/s12874-026-02861-w","DOIUrl":"https://doi.org/10.1186/s12874-026-02861-w","url":null,"abstract":"","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147762249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How to design a ROCI (Response Over Continuous Intervention) randomised trial: guidance and a case study.","authors":"Matteo Quartagno, Ehsan Ghorani, Tim P Morris, Henry Bern, Michelle N Clements, A Sarah Walker, James R Carpenter, Ian W White, Koen B Pouwels, Michael J Seckl, Mahesh Kb Parmar","doi":"10.1186/s12874-026-02786-4","DOIUrl":"https://doi.org/10.1186/s12874-026-02786-4","url":null,"abstract":"","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147762211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Cartesian Gaussian additive noise model for directed network inference in omics data.","authors":"Bailey Andrew, David R Westhead, Luisa Cutillo","doi":"10.1186/s12874-026-02849-6","DOIUrl":"https://doi.org/10.1186/s12874-026-02849-6","url":null,"abstract":"","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147762244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparing methods for handling missing data in electronic health records for dynamic risk prediction of central-line associated bloodstream infection.","authors":"Shan Gao, Elena Albu, Pieter Stijnen, Frank Rademakers, Veerle Cossey, Yves Debaveye, Christel Janssens, Ben Van Calster, Laure Wynants","doi":"10.1186/s12874-026-02819-y","DOIUrl":"https://doi.org/10.1186/s12874-026-02819-y","url":null,"abstract":"","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147762237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reporting of dog-assisted intervention trials: extension of the SPIRIT 2025 and CONSORT 2025 statement.","authors":"Sophie S Hall, Emily Shoesmith, Evgenia Riga, Daniel S Mills, Selina Gibsone, Dean McMillan, Qi Wu, Chris Clarke, Elena Ratschen","doi":"10.1186/s12874-026-02848-7","DOIUrl":"https://doi.org/10.1186/s12874-026-02848-7","url":null,"abstract":"","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147728350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic review of sample size determination in Bayesian randomized clinical trials: full Bayesian methods are rarely used.","authors":"Yanara Marks, Jessie Cunningham, Arlene Jiang, Linke Li, Yi-Shu Lin, Abigail McGrory, Yongdong Ouyang, Nam-Anh Tran, Yuning Wang, Anna Heath","doi":"10.1186/s12874-026-02854-9","DOIUrl":"https://doi.org/10.1186/s12874-026-02854-9","url":null,"abstract":"","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147716128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-derived constrained conditional model for screening marker genes through integrated high-throughput transcriptome big data.","authors":"Xiaobei Zhou, Jing Wan, Na Lv, Wensu Liu","doi":"10.1186/s12874-026-02851-y","DOIUrl":"https://doi.org/10.1186/s12874-026-02851-y","url":null,"abstract":"","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147716308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A causal inference framework for poststratification: a method for improving external validity in epidemiological studies.","authors":"Yeon Woo Oh, Dongkyu Lee, Jaelim Cho, Changsoo Kim, Kyoung-Nam Kim","doi":"10.1186/s12874-026-02835-y","DOIUrl":"https://doi.org/10.1186/s12874-026-02835-y","url":null,"abstract":"","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147697477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lessons learned from a door-to-door screening program for developmental delay and motor impairment in children in Cuenca, Ecuador.","authors":"Lourdes Huiracocha-Tutiven, Glen Newell, Jonathan Tipán Barros, Diana Patricia Vanegas Coveña, Mónica Marlene Mogrovejo Barros, Mabel Marín Dávila, Maritza Pintado Andrade, Ximena Bermeo Guartambel","doi":"10.1186/s12874-026-02837-w","DOIUrl":"https://doi.org/10.1186/s12874-026-02837-w","url":null,"abstract":"","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147687386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From chaos to clarity: schema-constrained AI for auditable biomedical evidence extraction from full-text PDFs.","authors":"Pouria Mortezaagha, Joseph Shaw, Bowen Sun, Arya Rahgozar","doi":"10.1186/s12874-026-02847-8","DOIUrl":"https://doi.org/10.1186/s12874-026-02847-8","url":null,"abstract":"<p><strong>Background: </strong>Biomedical evidence synthesis depends on accurate extraction of methodological, laboratory, and outcome variables from full-text research articles. These variables are predominantly embedded in complex scientific PDFs that interleave multi-column text, tables, figures, and captions, making manual abstraction time-intensive, error-prone, and increasingly impractical at the scale of contemporary systematic reviews. Despite advances in layout-aware and multimodal document models, end-to-end extraction systems suitable for evidence synthesis remain constrained by limited throughput, OCR error propagation, and insufficient auditability.</p><p><strong>Methods: </strong>We propose a schema-constrained AI extraction system that transforms full-text biomedical PDFs into structured, analysis-ready records by explicitly restricting model inference through typed schemas, controlled vocabularies, and evidence-gated decisions. Documents are ingested using resume-aware hashing, partitioned into page-level and caption-aware chunks, and processed asynchronously under explicit concurrency and rate-limiting controls. A high-accuracy OCR model is guided by multiple domain-specific schemas covering bibliographic metadata, study design, populations, laboratory assays, timing and thresholds, clinical outcomes, and diagnostic performance. Chunk-level outputs are deterministically merged into study-level records using controlled vocabularies, conflict-aware handling of scalar fields, set-based aggregation of list-valued fields, and sentence-level evidence capture to enable traceability and post-hoc audit.</p><p><strong>Results: </strong>Applied to a corpus of 734 biomedical articles on direct oral anticoagulant (DOAC) level measurement, the pipeline processed all documents without manual intervention while maintaining stable throughput. Schema-constrained extraction exhibited strong internal consistency, with sentence-level provenance populated for nearly all supported decisions. Iterative schema and prompt refinement yielded substantial improvements in extraction fidelity, particularly for outcome definitions, assay classification, and global coagulation testing. Outputs included reproducible CSV/Parquet datasets and caption-aware multimodal markdown reconstructions supporting efficient expert review.</p><p><strong>Conclusions: </strong>Schema-constrained AI extraction enables scalable and auditable extraction of structured evidence from heterogeneous scientific PDFs. By combining deterministic chunking, asynchronous orchestration, controlled vocabularies, sentence-level provenance, and aggregated analytical outputs, the proposed pipeline aligns modern document understanding capabilities with the transparency, reproducibility, and reliability demands of biomedical evidence synthesis.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147670457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}