By Associate Professor Blanca Gallego Luxan

Preprints

Greenberg JD; Huberts LCE; Ritchie A; Ooi S-Y; Flynn GM; Hart GK; Gallego Luxan BD, 2024, Improved Sensitivity For Detection Of Clinical Deterioration When Diagnostic Pathology And Patient Trends Are Included In Machine Learning Models, http://dx.doi.org/10.1101/2024.10.20.24315403

Blake V; Jorm L; Yu J; Lee A; Gallego B; Ooi S-Y, 2023, The Cardiac Analytics and Innovation (CardiacAI) Data Repository: An Australian data resource for translational cardiovascular research, http://dx.doi.org/10.48550/arxiv.2304.09341

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), http://dx.doi.org/10.2196/preprints.46322

Quiroz JC; Brieger D; Jorm L; Sy RW; Hsu B; Gallego B, 2022, Predicting adverse outcomes following catheter ablation treatment for atrial fibrillation, http://dx.doi.org/10.1016/j.hlc.2023.12.016

Sakal C; Hwang H; Quiroz JC; Gallego B, 2022, TreatmentEstimatoR: a Dashboard for Estimating Treatment Effects from Observational Health Data, http://dx.doi.org/10.48550/arxiv.2203.10458

Hwang H; Quiroz JC; Gallego B, 2021, Assessing The Effectiveness of Empirical Calibration Under Different Bias Scenarios, http://dx.doi.org/10.21203/rs.3.rs-1058822/v1

Hwang H; Quiroz JC; Gallego B, 2021, Assessing the effectiveness of empirical calibration under different bias scenarios, http://dx.doi.org/10.48550/arxiv.2111.04233

Liu J; Gallego B; Barbieri S, 2021, Incorporating Uncertainty in Learning to Defer Algorithms for Safe Computer-Aided Diagnosis, http://dx.doi.org/10.48550/arxiv.2108.07392

Gallego B; Zhu J, 2021, Time-to-event comparative effectiveness of NOACs vs VKAs in newly diagnosed non-valvular atrial fibrillation patients, http://dx.doi.org/10.1101/2021.08.06.21261092

Zhu J; Gallego B, 2021, Evolution of disease transmission rate during the course of SARS-COV-2: Patterns and determinants, http://dx.doi.org/10.21203/rs.3.rs-44647/v2

Kennedy G; Gallego B, 2021, Clinician Readiness to Adopt A.I. for Critical Care Prioritisation, http://dx.doi.org/10.1101/2021.02.11.21251604

Deng X; Feng Y; Sutjarittham T; Gharakheili HH; Gallego B; Sivaraman V, 2021, Comparing Broadband ISP Performance using Big Data from M-Lab, http://dx.doi.org/10.48550/arxiv.2101.09795

Quiroz J; Chard T; Sa Z; Ritchie A; Jorm L; Gallego B, 2021, Extract, Transform, Load Framework for the Conversion of Health Databases to OMOP, http://dx.doi.org/10.1101/2021.04.08.21255178

Khalifa M; Magrabi F; Gallego B, 2020, Validating and Updating GRASP: An Evidence-Based Framework for Grading and Assessment of Clinical Predictive Tools, http://dx.doi.org/10.21203/rs.3.rs-15929/v2

Zhu J; Gallego B, 2020, Evolution of disease transmission rate during the course of SARS-COV-2: Patterns and determinants, http://dx.doi.org/10.21203/rs.3.rs-44647/v1

Kennedy G; Rihari-Thomas J; Dras M; Gallego B, 2020, Developing a deep learning system to drive the work of the critical care outreach team, http://dx.doi.org/10.1101/2020.07.07.20148064

Castelyn G; Laranjo L; Schreier G; Gallego B, 2020, Predictive performance and impact of algorithms in remote monitoring of chronic conditions: a systematic review and meta-analysis (Preprint), http://dx.doi.org/10.2196/preprints.19253

Khalifa M; Magrabi F; Gallego B, 2020, Validating and Updating GRASP: An Evidence-Based Framework for Grading and Assessment of Clinical Predictive Tools, http://dx.doi.org/10.21203/rs.3.rs-15929/v1

Khalifa M; Magrabi F; Gallego B, 2019, Evaluating the Impact of Using GRASP Framework on Clinicians and Healthcare Professionals Decisions in Selecting Clinical Predictive Tools, http://dx.doi.org/10.48550/arxiv.1907.11523

Khalifa M; Magrabi F; Gallego B, 2019, Validating and Updating GRASP: A New Evidence-Based Framework for Grading and Assessment of Clinical Predictive Tools, http://dx.doi.org/10.48550/arxiv.1907.11524

Khalifa M; Magrabi F; Gallego B, 2019, Developing an Evidence-Based Framework for Grading and Assessment of Predictive Tools for Clinical Decision Support, http://dx.doi.org/10.48550/arxiv.1907.03706

Zhou N; Gallego B; Bao J; Tsafnat G, 2017, Pan-cancer scale landscape of simple somatic mutations, http://dx.doi.org/10.1101/112367

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