David Maslove, MD, MS, FRCPC

Researcher Name: 
David Maslove, MD, MS, FRCPC, Assistant Professor, Dept of Medicine, Queen’s University
Research Overview: 
Critical Care Informatics, CONDUIT Lab

 

Sepsis episodes

The care of patients in Intensive Care Units (ICUs) is a resource-intensive task, accounting for a substantial proportion of total health care costs. With few positive results emerging from randomized controlled trials, new approaches to research in this area are needed. The emergence of genome science presents an unprecedented opportunity to develop such novel approaches, based on understanding critical illness at a molecular level. Concurrently, advances in data science and the emergence of “big data” resources offer powerful new ways to conduct studies in genomics, and derive actionable evidence for clinical practices.

Our research aims include the development a novel database with the capacity to store and merge biomedical big data, as well as the analytic tools needed to translate raw data into medical knowledge. Our objectives include the development of knowledge representations of biomedical big data that will allow researchers at different sites to share data, and collaborate more effectively. We will also develop methods to collect clinical data from electronic medical records, as well as waveform data from bedside monitors, and to combine these using novel data structures.

Publications:

Electronic versus dictated hospital discharge summaries: a randomized controlled trial
DM Maslove, RE Leiter, J Griesman, C Arnott, O Mourad, CM Chow, ...
Journal of general internal medicine 24 (9), 995-1001

Gene expression profiling in sepsis: timing, tissue, and translational considerations
DM Maslove, HR Wong
Trends in molecular medicine 20 (4), 204-213

Identification of sepsis subtypes in critically ill adults using gene expression profiling
DM Maslove, BM Tang, AS McLean
Critical Care 16 (5), R183

A social network of hospital acquired infection built from electronic medical record data
M Cusumano-Towner, DY Li, S Tuo, G Krishnan, DM Maslove
Journal of the American Medical Informatics Association 20 (3), 427-434

Discretization of continuous features in clinical datasets
DM Maslove, T Podchiyska, HJ Lowe
Journal of the American Medical Informatics Association 20 (3), 544-553

Using information theory to identify redundancy in common laboratory tests in the intensive care unit
J Lee, DM Maslove
BMC Medical Informatics and Decision Making 15 (1), 59

Personalized Mortality Prediction Driven by Electronic Medical Data and a Patient Similarity Metric
J Lee, DM Maslove, JA Dubin

Customization of a Severity of Illness Score Using Local Electronic Medical Record Data
J Lee, DM Maslove
Journal of Intensive Care Medicine, 0885066615585951