Priya Deshpande, Alexander Rasin, Jacob Furst, Daniela Raicu, and Sameer Antani. Diis: A biomedical data access framework for aiding data driven research supporting fair principles. Data, 4(2):54, 2019.

Article  Google Scholar 

Priya Deshpande, Alexander Rasin, Tchoua Roselyne, Furst Jacob, Raicu Daniela, Schinkel Michiel, Trivedi Hari, and Antani Sameer. Biomedical heterogeneous data categorization and schema mapping towards data integration. Frontiers in Big Data, page yet to appear, 2023.

George Huo. Correlation indices: a new access method to exploit correlated attributes. PhD thesis, Massachusetts Institute of Technology, 2007.

P Deshpande, A Rasin, J Son, S Kim, E Brown, J Furst, DS Raicu, SM Montner, and SG Armato 3rd. Ontology-based radiology teaching file summarization, coverage, and integration. Journal of digital imaging, 2020.

RSNA. Rsna tfs. http://mirc.rsna.org/query, February 11, 2018.

Edward Weinberger, Rex Jakobovits, and Mark Halsted. Mypacs. net: a web-based teaching file authoring tool. American Journal of Roentgenology, 179(3):579–582, 2002.

ESR Neutorgasse. Eurorad. http://www.eurorad.org/, May 31, 2017.

NIH. Nih. https://nihcc.app.box.com/v/ChestXray-NIHCC/folder/36938765345, March, 8, 2019.

NIH. Nih. https://www.nih.gov/news-events/news-releases/, March, 8, 2019.

Les R Folio, Laura B Machado, and Andrew J Dwyer. Multimedia-enhanced radiology reports: concept, components, and challenges. RadioGraphics, 38(2):462–482, 2018.

Martin J Willemink, Wojciech A Koszek, Cailin Hardell, Jie Wu, Dominik Fleischmann, Hugh Harvey, Les R Folio, Ronald M Summers, Daniel L Rubin, and Matthew P Lungren. Preparing medical imaging data for machine learning. Radiology, 295(1):4–15, 2020.

RSNA. Radlex ontology. http://www.radlex.org/, February 11, 2018.

SNOMED International International Health Terminology Standards Development Organization. Snomedct ontology. http://www.snomed.org/, February 11, 2018.

Bioportal. Covid-19. https://bioportal.bioontology.org/ontologies/COVID-19, August 8, 2022.

Henning Müller, Nicolas Michoux, David Bandon, and Antoine Geissbuhler. A review of content-based image retrieval systems in medical applications—clinical benefits and future directions. International journal of medical informatics, 73(1):1–23, 2004.

Jennifer R Hemler, Jennifer D Hall, Raja A Cholan, Benjamin F Crabtree, Laura J Damschroder, Leif I Solberg, Sarah S Ono, and Deborah J Cohen. Practice facilitator strategies for addressing electronic health record data challenges for quality improvement: Evidencenow. The Journal of the American Board of Family Medicine, 31(3):398–409, 2018.

James J Cimino, Elaine J Ayres, Lyubov Remennik, Sachi Rath, Robert Freedman, Andrea Beri, Yang Chen, and Vojtech Huser. The national institutes of health’s biomedical translational research information system (btris): design, contents, functionality and experience to date. Journal of biomedical informatics, 52:11–27, 2014.

Ron Gutmark, Mark J Halsted, Laurie Perry, and Garry Gold. Use of computer databases to reduce radiograph reading errors. Journal of the American College of Radiology, 4(1):65–68, 2007.

Roland Talanow. Radiology teacher: a free, internet-based radiology teaching file server. Journal of the American College of Radiology, 6(12):871–875, 2009.

Article  PubMed  Google Scholar 

Priya Deshpande, Alexander Rasin, Eli Brown, Jacob Furst, Daniela Raicu, Steven Montner, and Samuel Armato III. An integrated database and smart search tool for medical knowledge extraction from radiology teaching files. In Medical Informatics and Healthcare, pages 10–18, 2017.

Priya Deshpande, Alexander Rasin, Eli Brown, Jacob Furst, Daniela S Raicu, Steven M Montner, and Samuel G Armato. Big data integration case study for radiology data sources. In 2018 IEEE Life Sciences Conference (LSC), pages 195–198. IEEE, 2018a.

Priya Deshpande, Alexander Rasin, Eli T Brown, Jacob Furst, Steven M Montner, Samuel G Armato III, and Daniela S Raicu. Augmenting medical decision making with text-based search of teaching file repositories and medical ontologies: Text-based search of radiology teaching files. International Journal of Knowledge Discovery in Bioinformatics (IJKDB), 8(2):18–43, 2018b.

CDM. Cdm. https://docs.microsoft.com/en-us/common-data-model/, November 8, 2022.

Health Level Seven International. Health level seven international. www.hl7.org, July 27,2018.

HL7FHIR. Hl7fhir. https://www.hl7.org/fhir/index.html, December, 18, 2020.

OHDSI. Ohdsi. https://www.ohdsi.org/data-standardization/the-common-data-model/, November 8, 2022.

cdisc. Cdisc. https://www.cdisc.org/standards/foundational/sdtm, June 18, 2021.

Ioana Manolescu. Integrating (very) heterogeneous data sources: A structured and an unstructured perspective. In European Conference on Advances in Databases and Information Systems, pages 15–20. Springer, 2020.

Teresa Martin-Carreras and Charles E Kahn Jr. Coverage and readability of information resources to help patients understand radiology reports. Journal of the American College of Radiology, 2017.

Peter Revesz and Thomas Triplet. Classification integration and reclassification using constraint databases. Artificial Intelligence in Medicine, 49(2):79–91, 2010.

Article  PubMed  Google Scholar 

Michael Stonebraker and Ihab F Ilyas. Data integration: The current status and the way forward. IEEE Data Eng. Bull., 41(2):3–9, 2018.

Stonebraker. tamr. https://www.tamr.com, August 8, 2022.

European Society of Radiology (ESR) communications@ myesr. org Marina Codari Luca Melazzini Sergey P. Morozov Cornelis C. van Kuijk Luca M. Sconfienza Francesco Sardanelli. Impact of artificial intelligence on radiology: a euroaim survey among members of the european society of radiology. Insights into imaging, 10:1–11, 2019.

Ketan Paranjape, Michiel Schinkel, and Prabath Nanayakkara. Short keynote paper: Mainstreaming personalized healthcare–transforming healthcare through new era of artificial intelligence. IEEE journal of biomedical and health informatics, 24(7):1860–1863, 2020.

PubMed  Google Scholar 

Wolfgang Orthuber. Information is selection—a review of basics shows substantial potential for improvement of digital information representation. International journal of environmental research and public health, 17(8):2975, 2020.

Article  PubMed  PubMed Central  Google Scholar 

Kristina K Gagalova, M Angelica Leon Elizalde, Elodie Portales-Casamar, and Matthias Görges. What you need to know before implementing a clinical research data warehouse: Comparative review of integrated data repositories in health care institutions. JMIR formative research, 4(8):e17687, 2020.

Helen Le Sueur, Ian N Bruce, and Nophar Geifman. The challenges in data integration–heterogeneity and complexity in clinical trials and patient registries of systemic lupus erythematosus. BMC Medical Research Methodology, 20(1):1–5, 2020.

mongodb. mongodb. https://www.mongodb.com/docs/, August 8, 2022.

cassandra. cassandra. https://cassandra.apache.org/doc/latest/, August 8, 2022.

Hbase. Hbase. https://hbase.apache.org/book.html, August 8, 2022.

CouchDB. Couchdb. https://docs.couchdb.org/en/3.2.2-docs/, August 8, 2022.

Thomas L Griffiths and Mark Steyvers. Finding scientific topics. Proceedings of the National academy of Sciences, 101(suppl 1):5228–5235, 2004.

Rajkumar Arun, Venkatasubramaniyan Suresh, CE Veni Madhavan, and MN Narasimha Murthy. On finding the natural number of topics with latent dirichlet allocation: Some observations. In Pacific-Asia conference on knowledge discovery and data mining, pages 391–402. Springer, 2010.

Juan Cao, Tian Xia, Jintao Li, Yongdong Zhang, and Sheng Tang. A density-based method for adaptive lda model selection. Neurocomputing, 72(7-9):1775–1781, 2009.

Article  Google Scholar 

David Mimno, Hanna Wallach, Edmund Talley, Miriam Leenders, and Andrew McCallum. Optimizing semantic coherence in topic models. In Proceedings of the 2011 conference on empirical methods in natural language processing, pages 262–272, 2011.

NIHNLM. Icd10. https://www.nlm.nih.gov/research/umls/sourcereleasedocs/current/ICD10CM/sourcerepresentation.html, Dec 10, 2019.

chexpert. chexpert. https://stanfordmlgroup.github.io/competitions/chexpert/, March, 8, 2019.