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Dr Oscar Perez Concha

Dr Oscar Perez Concha

Senior Lecturer

PhD Artificial Intelligence, Computer Science, Universidad Carlos III de Madrid, Spain, 2008

Medicine & Health
Centre for Big Data Research in Health

I am a health data scientist focused on improving healthcare processes and contributing to better patient outcomes. I specialise in analysing and extracting meaningful information from large unstructured health datasets using artificial intelligence (AI) and natural language processing (NLP). I currently lead research applying large language models (LLMs) and explainable AI to clinical text, with a focus on three key applications: improving the accuracy and efficiency of clinical coding, generating concise clinical summaries, and extracting clinically relevant information to support patient care.

I have a strong interest in teaching, learning, and the dissemination of AI in health. I founded and currently co-host the , (established in 2018) and co-organise the , both initiatives aimed at fostering interdisciplinary collaboration.聽I also teach and convene three postgraduate courses on applied AI in health, as part of the Master of Health Data Science and Clinical AI programs. I designed and created two of these courses: Health Data Analytics: Machine Learning I (HDAT9500), which introduces machine learning techniques for health data science research questions, and Health Data Analytics: Machine Learning II (HDAT9510), which focuses on deep learning methods for solving data science problems in healthcare.
E-mail
o.perezconcha@unsw.edu.au
  • Book Chapters | 2024
    Bi B; Liu L; Perez-Concha O, 2024, 'Adapting Large Language Models for Automated Summarisation of Electronic Medical Records in Clinical Coding', in , pp. 24 - 29,
    Book Chapters | 2012
    Gallego B; Concha 脫P; Lin FPY; Coiera EW, 2012, 'Exploring the role of pathology test results in the prediction of remaining days of hospitalisation.', in , pp. 45 - 50
    Book Chapters | 2008
    Patricio M; Berlanga A; Perez Concha O; Castanedo F; Garcia J; Molina JM, 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
    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 脡; 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 | 2024
    Bi B; Liu L; Lujic S; Jorm L; Concha 脫P, 2024, 'Harmonising the Clinical Melody: Tuning Large Language Models for Hospital Course Summarisation in Clinical Coding.', CoRR, abs/2409.14638
    Journal articles | 2024
    Kuo NIH; Perez-Concha O; Hanly M; Mnatzaganian E; Hao B; Di Sipio M; Yu G; Vanjara J; Valerie IC; de Oliveira Costa J; Churches T; Lujic S; Hegarty J; Jorm L; Barbieri S, 2024, 'Enriching Data Science and Health Care Education: Application and Impact of Synthetic Data Sets Through the Health Gym Project', JMIR Medical Education, 10,
    Journal articles | 2023
    Fitzgerald O; Concha 脫P; Luxan BG; Metke-Jimenez A; Rudd L; Jorm L, 2023, 'Continuous time recurrent neural networks: overview and application to forecasting blood glucose in the intensive care unit.', CoRR, abs/2304.07025
    Journal articles | 2023
    Fitzgerald O; Perez-Concha O; Gallego-Luxan B; Metke-Jimenez A; Rudd L; Jorm L, 2023, 'Continuous time recurrent neural networks: Overview and benchmarking at forecasting blood glucose in the intensive care unit', Journal of Biomedical Informatics, 146,
    Journal articles | 2023
    Fitzgerald O; Perez-Concha O; Gallego-Luxan B; Rudd L; Jorm L, 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', Scientific Reports, 13,
    Journal articles | 2023
    Liu L; Perez-Concha O; Nguyen A; Bennett V; Blake V; Gallego B; Jorm L, 2023, 'Web-Based Application Based on Human-in-the-Loop Deep Learning for Deidentifying Free-Text Data in Electronic Medical Records: Development and Usability Study.', Interact J Med Res, 12, pp. e46322,
    Journal articles | 2023
    Liu L; Perez-Concha O; Nguyen A; Bennett V; Jorm L, 2023, 'Automated ICD coding using extreme multi-label long text transformer-based models', Artificial Intelligence in Medicine, 144,
    Journal articles | 2023
    Roper L; He VY; Perez-Concha O; Guthridge S, 2023, 'Complex early childhood experiences: Characteristics of Northern Territory children across health, education and child protection data', PLoS ONE, 18,
    Journal articles | 2022
    Davies T; Louie JCY; Ndanuko R; Barbieri S; Perez-Concha O; Wu JHY, 2022, 'A Machine Learning Approach to Predict the Added-Sugar Content of Packaged Foods', Journal of Nutrition, 152, pp. 343 - 349,
    Journal articles | 2022
    Liu L; Concha 脫P; Nguyen AN; Bennett V; Jorm L, 2022, 'Automated ICD Coding using Extreme Multi-label Long Text Transformer-based Models.', CoRR, abs/2212.05857
    Journal articles | 2022
    Liu L; Concha 脫P; Nguyen AN; Bennett V; Jorm L, 2022, 'Hierarchical Label-wise Attention Transformer Model for Explainable ICD Coding.', CoRR, abs/2204.10716
    Journal articles | 2022
    Liu L; Perez-Concha O; Nguyen A; Bennett V; Jorm L, 2022, 'De-identifying Australian hospital discharge summaries: An end-to-end framework using ensemble of deep learning models', Journal of Biomedical Informatics, 135,
    Journal articles | 2022
    Liu L; Perez-Concha O; Nguyen A; Bennett V; Jorm L, 2022, 'Hierarchical label-wise attention transformer model for explainable ICD coding', Journal of Biomedical Informatics, 133,
    Journal articles | 2022
    Perez-Concha O; Goldstein D; Harris MF; Laaksonen MA; Hanly M; Suchy S; Vajdic CM, 2022, 'Uptake of Team Care Arrangements for adults newly diagnosed with cancer', Australian Journal of Primary Health, 29, pp. 20 - 29,
    Journal articles | 2021
    Fitzgerald O; Concha 脫P; Gallego B; Saxena MK; Rudd L; Metke-Jimenez A; Jorm L, 2021, 'Incorporating real-world evidence into the development of patient blood glucose prediction algorithms for the ICU.', J. Am. Medical Informatics Assoc., 28, pp. 1642 - 1650
    Journal articles | 2021
    Fitzgerald O; Perez-Concha O; Gallego B; Saxena MK; Rudd L; Metke-Jimenez A; Jorm L, 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,
    Journal articles | 2021
    Havard A; Barbieri S; Hanly M; Perez-Concha O; Tran DT; Kennedy D; Jorm LR, 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,
    Journal articles | 2021
    Liu L; Perez-Concha O; Nguyen A; Bennett V; Jorm L, 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,
    Journal articles | 2020
    Barbieri S; Kemp J; Perez-Concha O; Kotwal S; Gallagher M; Ritchie A; Jorm L, 2020, 'Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk', Scientific Reports, 10, pp. 1111,
    Journal articles | 2020
    Schaffer AL; Pearson SA; Perez-Concha O; Dobbins T; Ward RL; Leeuwen MTV; Rhee JJ; Laaksonen MA; Craigen G; Vajdic CM; van Leeuwen M, 2020, 'Diagnostic and health service pathways to diagnosis of cancer-registry notified cancer of unknown primary site (CUP)', PLoS ONE, 15, pp. e0230373,
    Journal articles | 2019
    Vajdic CM; Perez-Concha O; Dobbins T; Ward RL; Schaffer AL; van Leeuwen MT; Rhee JJ; Laaksonen MA; Craigen G; Pearson SA, 2019, 'Demographic, social and lifestyle risk factors for cancer registry-notified cancer of unknown primary site (CUP)', Cancer Epidemiology, 60, pp. 156 - 161,
    Journal articles | 2019
    Vajdic CM; Perez-Concha O; Rhee JJ; Dobbins T; Ward RL; Schaffer AL; van Leeuwen MT; Laaksonen MA; Craigen G; Pearson SA, 2019, 'Health-related predictors of cancer registry-notified cancer of unknown primary site (CUP)', Cancer Epidemiology, 61, pp. 1 - 7,
    Journal articles | 2018
    Arguel A; Perez-Concha O; Li SYW; Lau AYS, 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,
    Journal articles | 2018
    Maali Y; Perez-Concha O; Coiera E; Roffe D; Day RO; Gallego B, 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,
    Journal articles | 2016
    Cai X; Perez-Concha O; Coiera E; Martin-Sanchez F; Day R; Roffe D; Gallego B, 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,
    Journal articles | 2016
    Wang Y; Coiera E; Gallego B; Concha OP; Ong M; Tsafnat G; Roffe D; Jones G; Magrabi F, 2016, 'Measuring the effects of computer downtime on hospital pathology processes', Journal of biomedical informatics, 59, pp. 308 - 315
    Journal articles | 2015
    Gallego B; Magrabi F; Concha OP; Wang Y; Coiera E, 2015, 'Insights into temporal patterns of hospital patient safety from routinely collected electronic data', Health Information Science and Systems, 3, pp. s2,
    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,
    Journal articles | 2014
    Coiera E; Wang Y; Magrabi F; Concha OP; Gallego B; Runciman W, 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,
    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,
    Journal articles | 2013
    Borzeshi EZ; Concha OP; Xu RYD; Piccardi M, 2013, 'Joint action segmentation and classification by an extended hidden markov model', IEEE Signal Processing Letters, 20, pp. 1207 - 1210,
    Journal articles | 2013
    Gallego B; Runciman WB; Perez-Concha O; Liaw S; Day RO; Dunn AG; Coiera E; Liaw T, 2013, 'The management of severe hypertension in Australian general practice', BMC health services research, 13, pp. 414,
    Journal articles | 2011
    Otoom AF; Gunes H; Perez Concha O; Piccardi M, 2011, 'MLiT: Mixtures of Gaussians under Linear Transformations', Pattern Analysis and Applications, 14, pp. 193 - 205,
    Journal articles | 2008
    Garc铆a J; P茅rez 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,
    Journal articles | 2007
    Garcia J; Perez Concha O; Berlanga A; Molina JM, 2007, 'Video Tracking System Optimization using Evolution Strategies', International Journal of Imaging Systems and Technology, 17, pp. 75 - 90,
    Journal articles | 2007
    Patricio M; Carbo J; Perez Concha O; Molina JM, 2007, 'Multi-Agent Framework in Visual Sensor Networks', Eurasip journal on Advances in Signal Processing, 2007, pp. 98639-1 - 98639-21,
    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,
  • Preprints | 2025
    Lukmanjaya W; Butler T; Cox S; Perez-Concha O; Bromfield L; Karystianis G, 2025, Leveraging AI to Investigate Child Maltreatment Text Narratives: Promising Benefits and Addressable Risks (Preprint),
    Preprints | 2024
    Bi B; Liu L; Lujic S; Jorm L; Perez-Concha O, 2024, Harmonising the Clinical Melody: Tuning Large Language Models for Hospital Course Summarisation in Clinical Coding,
    Preprints | 2023
    Fitzgerald O; Perez-Concha O; Gallego-Luxan B; Metke-Jimenez A; Rudd L; Jorm L, 2023, Continuous time recurrent neural networks: overview and application to forecasting blood glucose in the intensive care unit, ,
    Preprints | 2023
    Fitzgerald O; Perez-Concha O; Gallego-Luxan B; Rudd L; Jorm L, 2023, Curation and description of a blood glucose management and nutritional support cohort using the eICU collaborative research database,
    Preprints | 2023
    Fitzgerald O; Perez-Concha O; Gallego-Luxan B; Rudd L; Jorm L, 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,
    Preprints | 2023
    Kuo NI-H; Perez-Concha O; Hanly M; Mnatzaganian E; Hao B; Di Sipio M; Yu G; Vanjara J; Valerie IC; de Oliveira Costa J; Churches T; Lujic S; Hegarty J; Jorm L; Barbieri S, 2023, Enriching Data Science and Health Care Education: Application and Impact of Synthetic Data Sets Through the Health Gym Project (Preprint),
    Preprints | 2023
    Liu L; Perez-Concha O; Nguyen A; Bennett V; Blake V; Gallego B; Jorm L, 2023, Web-Based Application Based on Human-in-the-Loop Deep Learning for Deidentifying Free-Text Data in Electronic Medical Records: Development and Usability Study (Preprint),
    Preprints | 2022
    Liu L; Perez-Concha O; Nguyen A; Bennett V; Jorm L, 2022, Automated ICD Coding using Extreme Multi-label Long Text Transformer-based Models,
    Preprints | 2022
    Liu L; Perez-Concha O; Nguyen A; Bennett V; Jorm L, 2022, Hierarchical Label-wise Attention Transformer Model for Explainable ICD Coding,
    Preprints | 2020
    Liu L; Perez-Concha O; Nguyen A; Bennett V; Jorm L, 2020, De-identifying Australian Hospital Discharge Summaries: An End-to-End Framework using Ensemble of Deep Learning Models, ,
    Preprints | 2019
    Barbieri S; Kemp J; Perez-Concha O; Kotwal S; Gallagher M; Ritchie A; Jorm L, 2019, Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk,
    Conference Abstracts | 2019
    Barbieri S; Perez Concha O; Kotwal S; Gallagher M; Ritchie A; Jorm L, 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
    Vajdic CM; Perez-Concha O; Rhee J; Dobbins T; Ward R; Schaffer A; Van Leeuwen MT; Laaksonen M; Craigen G; Pearson S, 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,
    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
    Zare borzeshi E; Perez Concha O; Piccardi M, 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
    Conference Papers | 2011
    Perez Concha O; Piccardi M; Yi da xu R; Moghaddam Z, 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,
    Conference Papers | 2010
    Otoom AF; Perez Concha O; Piccardi M, 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, presented at International Conference on Computer Vision Theory and Applications, Angers, France, 17 May 2010 - 21 May 2010
    Conference Papers | 2010
    Perez Concha O; Xu R; Piccardi M, 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,
    Conference Papers | 2010
    Xu R; Perez Concha O; Piccardi M, 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,
    Conference Papers | 2009
    Otoom AF; Perez Concha O; Gunes H; Piccardi M, 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,
    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,
    Conference Papers | 2007
    Perez Concha O; Piccardi M; Garcia J; Molina JM, 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,
    Conference Papers | 2007
    Piccardi M; Perez Concha O, 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,
    Conference Papers | 2007
    Piccardi M; Perez O, 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,
    Conference Papers | 2007
    P茅rez O; Piccardi M; Garc铆a 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,
    Conference Papers | 2006
    Garcia J; Perez Concha O; Molina JM; de Miguel G, 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,
    Conference Papers | 2006
    Perez Concha O; Garcia J; Molina JM, 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,
    Conference Papers | 2006
    Perez Concha O; Patricio M; Carbo J; Garcia J; Molina JM, 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,
    Conference Papers | 2006
    Perez Concha O; Patricio M; Garcia J; Molina JM, 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,
    Conference Papers | 2006
    Perez O; Patricio MA; Garcia J; Carbo J; Molina JM, 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,
    Conference Papers | 2005
    Perez Concha O; Garcia J; Berlanga A; Molina JM, 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,
    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,
    Conference Papers | 2005
    Rodriguez B; Perez Concha O; Garcia J; Molina JM, 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,
    Conference Papers |
    X. Cai, O. Perez-Concha, F. Martin-Sanchez, B. Gallego. , 'Modelling of Time Series Health Data using Dynamic Bayesian Networks: An application to predictions of patient outcomes after multiple surgeries.', in Proceedings of the Big Data Conference 2014, Melbourne

My Teaching

As part of of the MSc Health Data Science Program and the Clinical AI Program, I currently convene and teach the courses:

1. Health Data Analytics: Machine Learning I (HDAT9500) [Link]

Course Summary: This course provides an introduction to machine learning methods for addressing health research questions. You will learn how to formulate relevant questions and frame them as machine learning problems within a healthcare context. The course covers the fundamentals of key methods, including supervised learning (classification and regression) and unsupervised learning (dimensionality reduction and clustering). With a strong hands-on focus, the course equips you with the foundational skills and understanding needed to apply these methods to real-world healthcare data challenges.

2. Health Data Analytics: Machine Learning II (HDAT9510) [Link闭听

Course Summary: In this course, which builds upon a foundational understanding of machine learning, you will learn the core theory and practical application of deep learning algorithms in the area of health. Adopting a hands-on approach, the course is tailored to provide you with the essential skills and knowledge needed to effectively tackle and resolve healthcare data challenges using the deep learning algorithms covered in the course.

3. Health Data Science: Capstone (HDAT9910)聽[Link]

Course Summary: The capstone project involves completing extensive, desk-based, independent research tasks, requiring the use of the R and/or Python programming languages.聽 An entire health data science project聽has been constructed and sliced into the respective stages of the health data science pipeline, which you are required to complete.