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Researcher

Associate Professor Blanca Gallego Luxan

My Expertise

Clinical Analytics and Machine Learning

Big Data Analytics in Health

Predicting tools for clinical decision support

Keywords

Biography

Blanca Gallego Luxan PhD, MS, BS                                            Google Scholar Profile

Associate Professor Blanca Gallego Luxan leads a research unit in Clinical analytics and machine learning at the Centre for Big Data Research in Health, UNSW.

Trained as a physicist, Blanca obtained a PhD in climate modelling from the University of California, Los Angeles (UCLA). She then relocated to Australia where she worked at the University...view more

Blanca Gallego Luxan PhD, MS, BS                                            Google Scholar Profile

Associate Professor Blanca Gallego Luxan leads a research unit in Clinical analytics and machine learning at the Centre for Big Data Research in Health, UNSW.

Trained as a physicist, Blanca obtained a PhD in climate modelling from the University of California, Los Angeles (UCLA). She then relocated to Australia where she worked at the University of Sydney developing accounting frameworks for assessing the environmental impact of corporations. Blanca joined the Australian Institute of Health innovation (AIHI) in 2006. During her time at AIHI, she established a growing and successful research program in Health Analytics, developing and evaluating state-of-the-art techniques for clinical decision support, precision medicine, patient safety, and biosurveillance. In November 2017 she joined the Centre for Big Data Research as head of the Clinical Machine Learning Research Unit.


My Grants

  National Health and Medical Research Council (NHMRC) Grants

  • Centre for Research Excellence in Digital Health     Co-investigator $2,500,000 (2018-2022)
  • Research Project Grant in Precision Medicine         Lead investigator $520,967 (2017-2019)
  • Research Project Grant in Clinical Analytics            Lead investigator $312,000 (2013-2016)
  • Centre for Research Excellence in e-health             Co-investigator $2,500,000 (2011-2015)  

  Hearing Industry Research Consortium Grants

  • Large-scale clinical hearing rehabilitation data                      Co-investigator $150,00 (2015)

  St Vincent’s Clinic Foundation Grants

  • Predicting hospital readmission risk                                      Lead investigator $30,00 (2015)

  Australia-India Strategic Funds

  • Modelling Large-Scale Linked Data                                        Co-investigator $27,400 (2013)

  HCF Health and Medical Research Grant

  • An independent national clinical evidence service   Co-investigator $1,000,000 (2008-2009)

 


My Qualifications

  • PhD (2002), Climate Modelling, University of California Los Angeles (UCLA)
  • MS (1995), Quantum Chemistry, Autonoma University of Madrid
  • BS (1994), Physics, Autonoma University of Madrid
  • Postgraduate courses on Quantitative Financial Methods, University of Technology Sydney

My Awards

  • Best paper awards at international conferences    1999, 2009, 2012 and 2017
  • Researcher of the year award (AIHI)                                                           2015
  • Bjerkness Memorial award (UCLA)                                                             2002
  • Postgraduate Fellowships                                             1995, 1995-1998, 1999

My Research Activities

 

  • Enabling Personalised Cohort Studies from Large Repositories of Clinical Practice Data.
  • Aim: To design, develop and validate methods for the estimation of treatment effects for individual patients using EMR, ultimately supporting the practice of precision medicine.
  • Principal Investigators: Associate Professor Blanca Gallego Luxan, Elliott Zhu (PhD student)

 

  • Identification of patients at the end-of-life using HOMR Score at Prince of Wales Hospital
  • Aim: The main aim of this tool is to provide a platform that helps clinicians start discussions around symptom assessment and management and also to make sure that advance care directives are recorded in the EMR, ultimately improving care for end-of-life patients.
  • Principal Investigators: Dr Meg Sands (SESLHD – lead investigator), Associate Professor Blanca Gallego Luxan, Sarah-Jane Messum (SESLHD), Antony Kodsi.

 

  • Identification of cancer patients likely to have radiation treatment plan violations at North Shore Hospital.
  • Aim: The aim of this tool is to improve the quality and efficiency of developing radiation treatment plans.
  • Principal Investigators: Dr Thilo Schuler (NSLHD and PhD student leading this project), Associate Professor Blanca Gallego Luxan (supervisor), Professor Thomas Eade (Central Coast LHD), Dr John Kipritidis (NSLHD).

 

  • ‘watch list’ tool at St Vincent’s Hospital. This tool provides an automatically-populated list of patients at high risk of deterioration, and also serves as a valuable source of reliable information during ‘handover’ at each medical shift change.
  • Aim: The main aim of the watch list is to prevent unplanned ICU admissions and rapid response calls.
  • Principal investigators: Georgina Kennedy (PhD student leading this project), Associate Professor Blanca Gallego Luxan (supervisor), Rose Mary Kennedy (SESLHD).

 

  • Prediction of hypoglycemic events in ICU patients at Wollongong and John Hunters Hospital.
    Aim: The main aim of this tool is to improve existing blood glucose management protcols for ICU patients.
  • Current Status: This project commenced only a couple of months ago.
  • Principal Investigators: Dr Nikhil Kumar (Hunter New England LHD and PhD student leading this project), Associate Professor Blanca Gallego Luxan (supervisor), Dr Michael Davis (Illawara Shoalhaven LHD).

 

  • Platform to help clinicians choose and validate existing predictive tools in their local context.
  • Aim: To support safe, value-driven analytics tools in clinical practice and to increase the efficiency in the process of assessing and evaluating clinical predictive algorithms.
  • Principal Investigators: Associate Professor Blanca Gallego Luxan, Georgina Kennedy (PhD student).

 

  • GRASP Grading and Assessing Predictive tools for clinical decision support.
  • Aim: To provide clinicians and healthcare administrators with an objective, evidence-based approach to support their search and selection of cost-efffective clinical prediction tools. 
  • Principal Investigators: Dr Mohamed Khalifa (PhD student leading this project), Associate Professor Blanca Gallego Luxan (supervisor), Associate Professor Farah Magrabi (Co supervisor).

My Research Supervision


Supervision keywords


Areas of supervision

Clinical Analytics, Clinical Machine Learning, Big Data in Health, Causal inference in Health, Precision Medicine, Predictive Modelling, Clinical Decision Support, data-to-decision, observational studies using clinical practice data, learning health systems


Currently supervising

Georgina Kennedy (predicting clinical deterioration during hospitalisation)

Elliott Zhu (estimation of heterogenous treatment effects on survival outcomes)

Dr Mohamed Khalifa (supporting the choice of cost-effective predictive tools for clinical decision support)

Dr Thilo Schuler (data quality and predictive analytics to support decisions in radiation oncology)

Dr Nikhil Kumar (predicting hypoglycemic events in ICU patients)

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Contact

0405813314
0405813314