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Dr Oscar Perez Concha
Senior Research Fellow

Dr Oscar Perez Concha

PhD Computer Science

Medicine & Health
Centre for Big Data Research in Health

My research focuses on answering questions related to health and healthcare. I apply statistical and machine learning methods to large electronic health record datasets to identify patterns and explore outcomes for patient groups, improve patient care, and streamline clinical processes.

As part of of the MSc Health Data Science, I currently coordinate and teach the courses:

  1. Health Data Analytics: Machine Learning 1  (HDAT9500)
  2. Health Data Analytics: Machine Learning 2 (HDAT9510) 
E-mail
o.perezconcha@unsw.edu.au
  • Book Chapters | 2012
    2012, 'Exploring the role of pathology test results in the prediction of remaining days of hospitalisation.', in Maeder AJ; Martin Sanchez FJ (ed.), Studies in Health Technology and Informatics, Health Informatics: Building a Healthcare Future Through Trusted Information, IOS Press, Amsterdam, pp. 45 - 50, http://dx.doi.org/10.3233/978-1-61499-078-9-45
    Book Chapters | 2008
    2008, 'Computational Intelligence in Visual Sensor Networks. Improving Video Processing Systems', in Hassanien AE; Abraham A; Kacprzyk J (ed.), Studies in Computational Intelligence, Vol. 96: Computational Intelligence in Multimedia Proccesing. Recent Advances, Springer, Berlin, pp. 351 - 378, http://dx.doi.org/10.1007/978-3-540-76827-2_14
    Book Chapters | 2005
    Garcia J; Perez Concha O; Berlanga A; Molina JM, 2005, 'An Evolutionary Approach for Designing Multi-Target Tracking video Systems. Evaluation Metrics and Parameters Adjustment', in Cagnoni S; Lutton É; Olague G (ed.), Genetic and Evolutionary Computation for Image Processing and Analysis (EURASIP Book Series on Signal Processing and Communications), edn. First, Hindawi Publishing Corporation, New York NY, pp. 441 - 459
    Book Chapters | 2005
    Garcia J; Perez Concha O; Berlanga A; Molina JM, 2005, 'An evaluation metric for adjusting parameters of surveillance video systems', in Liu JX (ed.), Computer Vision and Robotics, edn. Original, Nova Science Publishers, New York, pp. 311 - 336
  • Journal articles | 2023
    2023, 'Complex early childhood experiences: Characteristics of Northern Territory children across health, education and child protection data', PLoS ONE, 18, http://dx.doi.org/10.1371/journal.pone.0280648
    Journal articles | 2022
    2022, 'A Machine Learning Approach to Predict the Added-Sugar Content of Packaged Foods', Journal of Nutrition, 152, pp. 343 - 349, http://dx.doi.org/10.1093/jn/nxab341
    Journal articles | 2022
    2022, 'De-identifying Australian hospital discharge summaries: An end-to-end framework using ensemble of deep learning models', Journal of Biomedical Informatics, 135, pp. 104215, http://dx.doi.org/10.1016/j.jbi.2022.104215
    Journal articles | 2022
    2022, 'Hierarchical label-wise attention transformer model for explainable ICD coding', Journal of Biomedical Informatics, 133, pp. 104161, http://dx.doi.org/10.1016/j.jbi.2022.104161
    Journal articles | 2022
    2022, 'Uptake of Team Care Arrangements for adults newly diagnosed with cancer', Australian Journal of Primary Health, 29, http://dx.doi.org/10.1071/py22078
    Journal articles | 2021
    2021, 'De-identifying Australian Hospital Discharge Summaries: An End-to-End Framework using Ensemble of Deep Learning Models', Journal of Biomedical Informatics, 135, pp. 104215, http://dx.doi.org/10.1016/j.jbi.2022.104215
    Journal articles | 2021
    2021, 'Incorporating real-world evidence into the development of patient blood glucose prediction algorithms for the ICU', Journal of the American Medical Informatics Association, 28, pp. 1642 - 1650, http://dx.doi.org/10.1093/jamia/ocab060
    Journal articles | 2021
    2021, 'Medications used disproportionately during pregnancy: Priorities for research on the risks and benefits of medications when used during pregnancy', Pharmacoepidemiology and Drug Safety, 30, pp. 53 - 64, http://dx.doi.org/10.1002/pds.5131
    Journal articles | 2020
    2020, 'Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk', Scientific Reports, 10, pp. 1111, http://dx.doi.org/10.1038/s41598-020-58053-z
    Journal articles | 2020
    2020, 'Diagnostic and health service pathways to diagnosis of cancer-registry notified cancer of unknown primary site (CUP)', PLoS ONE, 15, pp. e0230373, http://dx.doi.org/10.1371/journal.pone.0230373
    Journal articles | 2019
    2019, 'Demographic, social and lifestyle risk factors for cancer registry-notified cancer of unknown primary site (CUP)', Cancer Epidemiology, 60, pp. 156 - 161, http://dx.doi.org/10.1016/j.canep.2019.04.004
    Journal articles | 2019
    2019, 'Health-related predictors of cancer registry-notified cancer of unknown primary site (CUP)', Cancer Epidemiology, 61, pp. 1 - 7, http://dx.doi.org/10.1016/j.canep.2019.05.001
    Journal articles | 2018
    Arguel A; Perez-Concha O; Li SY W; Lau AY S, 2018, 'Theoretical approaches of online social network interventions and implications for behavioral change: a systematic review', Journal of Evaluation in Clinical Practice, 24, pp. 212 - 221, http://dx.doi.org/10.1111/jep.12655
    Journal articles | 2018
    2018, 'Predicting 7-day, 30-day and 60-day all-cause unplanned readmission: a case study of a Sydney hospital', BMC medical informatics and decision making, 18, pp. 1 - 11, http://dx.doi.org/10.1186/s12911-017-0580-8
    Journal articles | 2016
    2016, 'Measuring the effects of computer downtime on hospital pathology processes', Journal of biomedical informatics, 59, pp. 308 - 315, http://dx.doi.org/10.1016/j.jbi.2015.12.016
    Journal articles | 2016
    2016, 'Real-time prediction of mortality, readmission, and length of stay using electronic health record data', Journal of the American Medical Informatics Association, 23, pp. 553 - 561, http://dx.doi.org/10.1093/jamia/ocv110
    Journal articles | 2015
    Zhang Z; Concha OP; Piccardi M, 2015, 'Tracking people under heavy occlusions by layered data association', Multimedia Tools and Applications, 74, pp. 7239 - 7259, http://dx.doi.org/10.1007/s11042-014-1979-1
    Journal articles | 2015
    2015, 'Insights into temporal patterns of hospital patient safety from routinely collected electronic data', HEALTH INFORMATION SCIENCE AND SYSTEMS, 3, http://dx.doi.org/10.1186/2047-2501-3-S1-S2
    Journal articles | 2014
    Concha OP; Gallego B; Hillman K; Delaney GP; Coiera E, 2014, 'Do variations in hospital mortality patterns after weekend admission reflect reduced quality of care or different patient cohorts? A population-based study', BMJ quality & safety, 23, pp. 215 - 222, http://dx.doi.org/10.1136/bmjqs-2013-002218
    Journal articles | 2014
    2014, 'Predicting the cumulative risk of death during hospitalization by modeling weekend, weekday and diurnal mortality risks', BMC health services research, 14, pp. 226 - 226, http://dx.doi.org/10.1186/1472-6963-14-226
    Journal articles | 2013
    Borzeshi EZ; Concha OP; Xu RY D; Piccardi M, 2013, 'Joint action segmentation and classification by an extended hidden markov model', IEEE Signal Processing Letters, 20, pp. 1207 - 1210, http://dx.doi.org/10.1109/LSP.2013.2284196
    Journal articles | 2013
    2013, 'The management of severe hypertension in Australian general practice', BMC health services research, 13, pp. 414, http://dx.doi.org/10.1186/1472-6963-13-414
    Journal articles | 2011
    2011, 'MLiT: Mixtures of Gaussians under Linear Transformations', Pattern Analysis and Applications, 14, pp. 193 - 205, http://dx.doi.org/10.1007/s10044-011-0205-2
    Journal articles | 2008
    García J; Pérez O; Berlanga A; Molina JM, 2008, 'An evolutionary approach for designing multitarget tracking video systems', Eurasip Book Series on Signal Processing and Communications, 8, pp. 441 - 466
    Journal articles | 2008
    Rodriguez B; Perez Concha O; Garcia J; Molina JM, 2008, 'Machine Learning Techniques for acquiring new Knowledge in Image Tracking', Applied Artificial Intelligence, 22, pp. 266 - 282, http://dx.doi.org/10.1080/08839510701821652
    Journal articles | 2007
    2007, 'Multi-Agent Framework in Visual Sensor Networks', Eurasip journal on Advances in Signal Processing, 2007, pp. 98639-1 - 98639-21, http://dx.doi.org/10.1155/2007/98639
    Journal articles | 2007
    2007, 'Video Tracking System Optimization using Evolution Strategies', International Journal of Imaging Systems and Technology, 17, pp. 75 - 90, http://dx.doi.org/10.1002/ima.20100
    Journal articles | 2005
    Molina JM; Garcia J; Perez Concha O; Carbo J; Berlanga A; Portillo JI, 2005, 'Applying fuzzy logic in video surveillance systems', Mathware & Soft Computing, 12, pp. 185 - 198, https://eudml.org/doc/40867
  • Preprints | 2023
    2023, Continuous time recurrent neural networks: overview and application to forecasting blood glucose in the intensive care unit, , http://arxiv.org/abs/2304.07025v1
    Preprints | 2023
    2023, Curation and description of a blood glucose management and nutritional support cohort using the eICU collaborative research database, , http://dx.doi.org/10.1101/2023.04.20.23288845
    Preprints | 2023
    2023, DEFT: a web-based system for DE-identifying Free Text data in electronic medical records using human in the loop deep learning (Preprint), , http://dx.doi.org/10.2196/preprints.46322
    Preprints | 2023
    2023, The relationship between hyperglycaemia on admission and patient outcome is modified by hyperlactatemia and diabetic status: a retrospective analysis of the eICU collaborative research database, , http://dx.doi.org/10.1101/2023.05.01.23289339
    Preprints | 2022
    2022, Automated ICD Coding using Extreme Multi-label Long Text Transformer-based Models, , http://arxiv.org/abs/2212.05857v2
    Preprints | 2022
    2022, Hierarchical Label-wise Attention Transformer Model for Explainable ICD Coding, , http://dx.doi.org/10.1016/j.jbi.2022.104161
    Preprints | 2020
    2020, De-identifying Australian Hospital Discharge Summaries: An End-to-End Framework using Ensemble of Deep Learning Models, , http://dx.doi.org/10.48550/arxiv.2101.00146
    Conference Abstracts | 2019
    2019, 'A Deep Representation of Longitudinal EMR Data Used for Predicting Readmission to the ICU and Describing Patients-at-Risk', in HSRAANZ, Auckland, New Zealand, presented at HSRAANZ, Auckland, New Zealand
    Conference Abstracts | 2019
    2019, 'Risk factors for cancer registry-notified cancer of unknown primary site (CUP)', in Asia Pacific Journal of Clinical Oncology, Wiley, Adelaide, Vol. 15, pp. 84 - 85, presented at Clinical Oncology Society of Australia 46th Annual Scientific Meeting, Adelaide, 12 November 2019 - 14 November 2019, http://dx.doi.org/10.1111/ajco.13262
    Preprints | 2019
    2019, Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk, , http://dx.doi.org/10.48550/arxiv.1905.08547
    Conference Papers | 2014
    2014, 'Modelling of Time Series Health Data using Dynamic Bayesian Networks: An application to predictions of patient outcomes after multiple surgeries.', in Barbuto K; Schaper L; Verspoor K (eds.), Proceedings of the Big Data Conference 2014, Melbourne, Melbourne, Australia, pp. 22 - 23, presented at Big Data 2014, Melbourne, Australia, 03 April 2014 - 04 April 2014, https://hisa.site-ym.com/page/bigdata2014
    Conference Papers | 2013
    Luxan BG; Magrabi F; Concha OP; Wang Y; Coiera E, 2013, 'Insights into patterns of healthcare delivery from hospital electronic medical records', in HISA Big Data in Biomedicine and Healthcare 2013 conference, Health Informatics Society of Australia, Melbourne, presented at Big Data in Health and Biomedicine, Melbourne, 18 April 2013 - 19 April 2013
    Conference Papers | 2012
    2012, 'Human Action Recognition in Video by Fusion of Structural and Spatio-Temporal Features', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Volume 7626, Springer Verlag, Hiroshima, Japan, November 7-9, 2012, pp. 474 - 482, presented at Joint IAPR International Workshops on Structural and Syntactic Pattern Recognition (SSPR 2012) and Statistical Techniques in Pattern Recognition (SPR 2012), Hiroshima, Japan, 07 November 2012 - 09 November 2012, http://dx.doi.org/10.1007/978-3-642-34166-3_52
    Conference Papers | 2011
    2011, 'HMM-MIO: an enhanced hidden Markov model for action recognition', in 2011 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), IEEE, Piscataway, NJ, United States, pp. 62 - 69, presented at Computer Vision and Pattern Recognition Workshops (CVPRW), Colorado Springs, CO, 20 June 2011 - 25 June 2011, http://dx.doi.org/10.1109/CVPRW.2011.5981803
    Conference Papers | 2010
    2010, 'Compressive Sensing of Time Series for Human Action Recognition', in International Conference on Digital Image Computing: Techniques and Applications, Proceedings, IEEE, Sydney, Australia, pp. 454 - 461, presented at Digital Image Computing: Techniques and Applications, Sydney, Australia, 01 December 2010 - 03 December 2010, http://dx.doi.org/10.1109/DICTA.2010.83
    Conference Papers | 2010
    2010, 'Mixtures of Gaussian Distributions under Linear Dimensionality Reduction', in Proceedings of the Fifth International Conference on Computer Vision Theory and Applications volume 2, Angers, France, pp. 511 - 518, presented at International Conference on Computer Vision Theory and Applications, Angers, France, 17 May 2010 - 21 May 2010
    Conference Papers | 2010
    2010, 'Robust Dimensionality Reduction for Human Action Recognition', in International Conference on Digital Image Computing: Techniques and Applications, Proceedings, IEEE, Sydney, Australia, pp. 349 - 356, presented at Digital Image Computing: Techniques and Applications, Sydney, Australia, 01 December 2010 - 03 December 2010, http://dx.doi.org/10.1109/DICTA.2010.66
    Conference Papers | 2009
    2009, 'Mixtures of Normalized Linear Projections', in Lecture Notes in Computer Science vol. 5807, Springer-Verlag, Berlin, pp. 66 - 76, presented at Advanced Concepts for Intelligent Vision Systems. Lectures Notes on Computer Science, Mercure Chateau Chartrons, Bordeaux, France, 28 September 2009 - 02 October 2009, http://dx.doi.org/10.1007/978-3-642-04697-1_7
    Conference Papers | 2007
    Perez Concha O; Piccardi M; Garcia J; Molina JM, 2007, 'Comparison between Genetic Algorithms and Baum-Welch algorithm for the adjustment of HMM to Classify Human Activities', in Lecture Notes in Computer Science vol. 4448, Springer-Verlag, Berlin, pp. 399 - 406, presented at Ninth European Workshop on Evolutionary Computation in Image Analysis and Signal Processing, Valencia, Spain, 11 April 2007 - 13 April 2007, http://dx.doi.org/10.1007/978-3-540-71805-5
    Conference Papers | 2007
    Pérez O; Piccardi M; García J; Patricio MA; Molina JM, 2007, 'Comparison between genetic algorithms and the Baum-Welch algorithm in learning HMMs for human activity classification', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 399 - 406, http://dx.doi.org/10.1007/978-3-540-71805-5_44
    Conference Papers | 2007
    2007, 'Comparison of Classifiers for Human Activity Recognition', in Lecture Notes in Computer Science vol. 4528, Springer-Verlag, Berlin, pp. 192 - 201, presented at Second Work-Conference on the Interplay between Natural and Artificial Computation, Murcia, Spain, 18 June 2007 - 21 June 2007, http://dx.doi.org/10.1007/978-3-540-73055-2
    Conference Papers | 2007
    2007, 'Hidden Markov Models with Kernel Density Estimation of Emission Probabilities and their Use in Activity Recognition', in IEEE conference on computer vision and pattern recognition 2007, Minneapolis, MN, pp. 1 - 8, presented at IEEE Conference on Computer Vision and Pattern Recognition, 2007, Minneapolis, MN, 17 June 2007 - 22 June 2007, http://dx.doi.org/10.1109/CVPR.2007.383504
    Conference Papers | 2007
    2007, 'Hidden Markov models with kernel density estimation of emission probabilities and their use in activity recognition', in 2007 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOLS 1-8, IEEE, MN, Minneapolis, pp. 3774 - +, presented at IEEE Conference on Computer Vision and Pattern Recognition, MN, Minneapolis, 17 June 2007 - 22 June 2007, https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000250382807056&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a29b250adbe88d1
    Conference Papers | 2006
    2006, 'Fusion of Surveillance Information for Visual Sensor Networks', in 9th International Conference on Information Fusion, IEEE, Florence, Italy, pp. 1 - 8, presented at The 9th International Conference on Information Fusion, Florence, Italy, 10 July 2006 - 14 July 2006, http://dx.doi.org/10.1109/ICIF.2006.301602
    Conference Papers | 2006
    2006, 'Fusion of surveillance information for visual sensor networks', in 2006 9TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, VOLS 1-4, IEEE, ITALY, Florence, pp. 302 - 309, presented at 9th International Conference on Information Fusion, ITALY, Florence, 10 July 2006, https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000245998000042&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a29b250adbe88d1
    Conference Papers | 2006
    2006, 'Improving the Segmentation Stage of a Pedestrian Tracking Video-Based System by Means of Evolution Strategies', in Lecture Notes in Computer Science vol. 3907, Springer-Verlag, Berlin, pp. 438 - 449, presented at The Eighth European Workshop on Evolutionary Computation in Image Analysis and Signal Processing, Budapest, Hungary, 10 April 2006 - 12 April 2006, http://dx.doi.org/10.1007/11732242_39
    Conference Papers | 2006
    2006, 'Neuro-fuzzy Learning Applied to Improve the Trajectory Reconstruction Problem', in Computational Intelligence for Modelling, Control and Automation, 2006 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on, IEEE, Sydney, pp. 4 - 4, presented at International Conference on Computational Intelligence for Modelling, Control and Automation, Sydney, 28 November 2006 - 01 December 2006, http://dx.doi.org/10.1109/CIMCA.2006.157
    Conference Papers | 2006
    2006, 'Trajectory classification based on machine-learning techniques over tracking data', in 9th International Conference on Information Fusion, IEEE, Florence, Italy, pp. 1 - 8, presented at The 9th International Conference on Information Fusion, Florence, Italy, 10 July 2006 - 14 July 2006, http://dx.doi.org/10.1109/ICIF.2006.301629
    Conference Papers | 2005
    Perez Concha O; Garcia J; Berlanga A; Molina JM, 2005, 'Evolving Parameters of Surveillance video Systems for Non-Overfitting Learning', in Lecture Notes in Computer Science , Vol. 3449, Springer-Verlag, Lausanne, Switzerland, pp. 386 - 395, presented at In The Seventh European Workshop on Evolutionary Computation in Image Analysis and Signal Processing, Lausanne, Switzerland, 30 March 2005 - 01 April 2005, http://dx.doi.org/10.1007/978-3-540-32003-6_39
    Conference Papers | 2005
    2005, 'Adjustment of Surveillance Video Systems by a Performance Evaluation Function', in Lecture Notes in Computer Science vol. 3562, Springer-Verlag, Berlin, pp. 499 - 508, presented at First Internacional Work-Conference on the Interplay between Natural and Artificial Computation, Las Palmas, Spain, 15 June 2005 - 18 June 2005, http://dx.doi.org/10.1007/11499305_51
    Conference Papers | 2005
    2005, 'Application of Machine Learning Techniques for Simplifying the Association Problem in a Video Surveillance System', in Lecture Notes in Computer Science vol. 3562, Springer-Verlag, Berlin, pp. 509 - 518, presented at First Internacional Work-Conference on the Interplay between Natural and Artificial Computation, Las Palmas, Spain, 15 June 2005 - 18 June 2005, http://dx.doi.org/10.1007/b137296

My Research Supervision

2 PhD students

My Teaching

  1. Machine Learning I - HDAT9500 (MSc Health Data Science)
  2. Machine Learning II - HDAT9510 (MSc Health Data Science - new course 2022).