Jessilyn Dunn
Cardiology and Cardiovascular Medicine · 2019–2020
A researcher in the Science corpus: 3 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Cardiology and Cardiovascular Medicine — 12 citations into it
- Biomedical Engineering — 5 citations into it
Whom Jessilyn Dunn trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- F. Shaffer (in Biomedical Engineering)
- J. Ginsberg (in Biomedical Engineering)
Papers from Jessilyn Dunn's perspective
Ordered by how strongly the researchers Jessilyn Dunn trusts endorse each paper. Same corpus, a different order for every researcher.
- The max-min hill-climbing Bayesian network structure learning algorithm
- Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. (European Heart Journal-Cardiovascular Imaging)
- TopHat: discovering splice junctions with RNA-Seq (Bioinform.)
- An Overview of Heart Rate Variability Metrics and Norms (Frontiers in Public Health)
- A review on wearable photoplethysmography sensors and their potential future applications in health care (International Journal of Biosensors & Bioelectronics)
- Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. (The Lancet Diabetes and Endocrinology)
- Accuracy in Wrist-Worn, Sensor-Based Measurements of Heart Rate and Energy Expenditure in a Diverse Cohort (bioRxiv)
- Personal Omics Profiling Reveals Dynamic Molecular and Medical Phenotypes (Cell)
- Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics (Genetics in Medicine)
- Sex differences in healthy human heart rate variability: A meta-analysis. (Neuroscience and Biobehavioral Reviews)
Their papers
- A Longitudinal Big Data Approach for Precision Health (2019) — 362 citations
- Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs) (2020) — 429 citations
- Investigating sources of inaccuracy in wearable optical heart rate sensors (2020) — 598 citations