Gavin E. Duggan
Veterans Health Administration
Deep learningStatistical modelMachine learningInternal medicineEndocrinologyMetabolomeArtificial intelligenceHuman genomeInteroperabilityData pointMetabolomicsMetaboliteWeaningMetabolic profileComputer scienceObesityMedical diagnosisBiochemistryComputational biologyMedicineBiology
17Publications
13H-index
4,104Citations
Publications 15
Newest
#1Esther A. H. Warnert (EUR: Erasmus University Rotterdam)H-Index: 6
#2Lars Kasper (UZH: University of Zurich)H-Index: 18
Last. Udunna C. Anazodo (UWO: University of Western Ontario)H-Index: 9
view all 12 authors...
Source
#1Anna MajkowskaH-Index: 1
#2Sid MittalH-Index: 1
Last. Shravya ShettyH-Index: 8
view all 14 authors...
Four deep learning models identified pneumothorax, fractures, opacity, and nodule or mass on frontal chest radiographs with similar performance to radiologists.
73 CitationsSource
#1Alvin Rajkomar (UCSF: University of California, San Francisco)H-Index: 11
#2Eyal Oren (Google)H-Index: 20
Last. Mimi Sun (Google)H-Index: 4
view all 35 authors...
Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality. Constructing predictive statistical models typically requires extraction of curated predictor variables from normalized EHR data, a labor-intensive process that discards the vast majority of information in each patient’s record. We propose a representation of patients’ entire raw EHR records based on the Fast Healthcare Interoperability Resources (FHIR) forma...
806 CitationsSource
#1Alvin Rajkomar (UCSF: University of California, San Francisco)H-Index: 5
#1Alvin RajkomarH-Index: 11
Last. Jeffrey Dean (Google)H-Index: 63
view all 34 authors...
Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality. Constructing predictive statistical models typically requires extraction of curated predictor variables from normalized EHR data, a labor-intensive process that discards the vast majority of information in each patient’s record. We propose a representation of patients’ entire raw EHR records based on the Fast Healthcare Interoperability Resources (FHIR) forma...
526 CitationsSource
#1Verena HoerrH-Index: 14
#2Gavin E. Duggan (U of C: University of Calgary)H-Index: 13
Last. Hans J. Vogel (U of C: University of Calgary)H-Index: 67
view all 9 authors...
Background The emergence of antibiotic resistant pathogenic bacteria has reduced our ability to combat infectious diseases. At the same time the numbers of new antibiotics reaching the market have decreased. This situation has created an urgent need to discover novel antibiotic scaffolds. Recently, the application of pattern recognition techniques to identify molecular fingerprints in ‘omics’ studies, has emerged as an important tool in biomedical research and laboratory medicine to identify pat...
44 CitationsSource
#1Beata Mickiewicz (U of C: University of Calgary)H-Index: 9
#2Gavin E. DugganH-Index: 13
Last. Hans J. VogelH-Index: 67
view all 6 authors...
Objectives:To determine whether a nuclear magnetic resonance–based metabolomics approach can be useful for the early diagnosis and prognosis of septic shock in ICUs.Design:Laboratory-based study.Setting:University research laboratory.Subjects:Serum samples from septic shock patients and ICU controls
63 CitationsSource
#1Sean C. Booth (U of C: University of Calgary)H-Index: 8
#2Iain George (U of C: University of Calgary)H-Index: 4
Last. Raymond J. Turner (U of C: University of Calgary)H-Index: 60
view all 7 authors...
Bioremediation efforts worldwide are faced with the problem of metals interfering with the degradation of organic pollutants. There has been little systematic investigation into how the important environmental factors of media composition, buffering agent, and carbon source affect the exertion of metal toxicity on bacteria. This study aimed to systematically separate and investigate the influence of these factors by examining planktonic and biofilm establishment and growth. Two Pseudomonads were...
23 CitationsSource
Source
#1Gavin E. Duggan (U of C: University of Calgary)H-Index: 13
#2Dustin S. Hittel (U of C: University of Calgary)H-Index: 24
Last. Jane Shearer (U of C: University of Calgary)H-Index: 34
view all 6 authors...
This study determined whether targeted metabolomic profiling of serum, using 1H nuclear magnetic resonance, could be employed to distinguish the effects of obesity from those of diet in mice. Following weaning, littermates were randomly divided into two diet groups: chow and high fat. After 12 weeks of dietary manipulation, fat-fed animals were obese and hyperglycaemic. Mice from each treatment either maintained their current diet or switched to the opposite diet for a final week. Differences in...
34 CitationsSource
#1Gavin E. Duggan (U of C: University of Calgary)H-Index: 13
#2B. Joan Miller (U of C: University of Calgary)H-Index: 5
Last. H J Vogel (U of C: University of Calgary)
view all 4 authors...
Nutrient deficiencies are an ongoing problem in many populations and ascorbic acid is a key vitamin whose mild or acute absence leads to a number of conditions including the famously debilitating scurvy. As such, the biochemical effects of ascorbate deficiency merit ongoing scrutiny, and the Gulo knockout mouse provides a useful model for the metabolomic examination of vitamin C deficiency. Like humans, these animals are incapable of synthesizing ascorbic acid but with dietary supplements are ot...
8 CitationsSource