Development of Artificial Intelligence-Driven in Clinical Decision Support Systems

Chih-Lin, C. (2019). Medical decision support systems based on machine learning. PhD (Doctor of Philosophy) thesis, University of Iowa, https://doi.org/10.17077/etd.o5gmwvxk Rosse, C. ,Mejino,J.L.V. (2019). A reference ontology for biomedical informatics: the Foundational Model of AnatomyJ Biomed Inform, 36 (2003), pp. 478-500 Article Download PDFView Record in Scopus Google Scholar Ouwens, M. ,Wollersheim, H. , Hermens, R. , Hulscher, M. , Grol,R. (2015). Integrated care programmes for chronically ill patients: a review of systematic reviews. Int J Qual Health- Care, 17 (2) (2005), pp. 141-146 Bianchi,S. et al., (2019). Biomedical data integration - capturing similarities while preserving disparities, Conf. Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. IEEE Eng. Med. Biol. Soc. Annu. Conf., vol. 2019, pp. 4654–4657, 2019. Heldt,T. and Verghese, G. C. (2019). Model-based data integration in clinical environments, Conf. Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. IEEE Eng. Med. Biol. Soc. Annu.Conf., vol. 2019, pp. 5209–5212, 2010. Alexander, P., Joseph, L.(2020). Multi Agent Enhanced Business Intelligence for Localized Automatic Pricing in Grocery Chains. A dissertation submitted in fulfillment of the requirements of the degree of Doctor of Philosophy for the School of Information Technology, Bond University. December 2011. www.fulltext.pdf/ Retrieved on August 13, 2017 Ying Yang And Tao Chen (2019) . Analysis and Visualization Implementation of Medical Big Data Resource Sharing Mechanism Based on Deep Learning. School of Management, Xinxiang Medical University, Xinxiang 453003, China 2The Third Affiliated Hospital of Xinxiang Medical University, Xinxiang 453003, China Awais, A. (2019). Predicting clinical outcomes via machine learning on electronic health records.Halmstad University Dissertations no. 58 ISBN 978-91-88749-24-6 (printed) ISBN 978-91-88749-25-3 (pdf) Publisher: Halmstad University Press Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q Weinberger (2017). On calibration of modern neural networks. In International conference on machine learning, pages 1321–1330. PMLR, 2017. Jeremy Nixon, Michael W Dusenberry, Linchuan Zhang, Ghassen Jerfel, and Dustin Tran (2019). Measuring calibration in deep learning. In CVPR workshops, volume 2. Anne AH de Hond, Artuur M Leeuwenberg, Lotty Hooft, Ilse MJ Kant, Steven WJ Nijman, Hendrikus JA van Os, Jiska J Aardoom, Thomas PA Debray, Ewoud Schuit, Maarten van Smeden (2022). Guidelines and quality criteria for artificial intelligence-based prediction models in healthcare: a scoping review. NPJ digital medicine, 5(1):2. Michelle M Amri, Geneviève Jessiman-Perreault, Arjumand Siddiqi, Patricia O’Campo, Theresa Enright, and Erica Di Ruggiero (2021). Scoping review of the world health organization’s underlying equity discourses: apparent ambiguities, inadequacy, and contradictions. International Journal for Equity in Health, 20(1):70. Solon Barocas and Andrew D Selbst (2016). Big data’s disparate impact. Calif. L. Rev., 104:671. Ziad Obermeyer, Brian Powers, Christine Vogeli, and Sendhil Mullainathan (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464):447–453. Oscar Schwartz (2019). Untold history of Artifical Intelligent: Algorithmic bias was born in the 1980s. IEEE Spectrum, 15. Maarten Van Smeden, Georg Heinze, Ben Van Calster, Folkert W Asselbergs, Panos E Vardas, Nico Bruining, Peter De Jaegere, Jason H Moore, Spiros Denaxas, Anne Laure Boulesteix (2022). Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease. European heart journal, 43(31):2921–2930. Ewout W Steyerberg and Yvonne Vergouwe (2014). Towards better clinical prediction models: seven steps for development and an abcd for validation. European heart journal, 35(29):1925–1931. Alexander, W. F. (2017). Improving Clinical Decision Making With Natural Language Processing And Machine Learning. Computer Science and Engineering at the Massachusetts Institute of Technology Awais, A. (2019). Predicting clinical outcomes via machine learning on electronic health records. Halmstad University Dissertations no. 58 ISBN 978-91-88749-24-6 (printed) ISBN 978- 91-88749-25-3 (PDF) Publisher: Halmstad University Press Jiang, S., Fang, S., Bloomquist, S., Keiper, J., Palakal, M., Xia, Y. and Grannis, S (2016). Healthcare Data Visualization: Geospatial and Temporal Integration. DOI: 10.5220/0005714002120219 In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications Volume 2: IVAPP, pages 214-221 ISBN: 978-989-758-175-5 Ying Yang And Tao Chen (2019). Analysis and Visualization Implementation of Medical Big Data Resource Sharing Mechanism Based on Deep Learning. School of Management, Xinxiang Medical University, Xinxiang 453003, China 2The Third Affiliated Hospital of Xinxiang Medical University, Xinxiang 453003, China