Gunnar Hartvigsen
Cardiology and Cardiovascular Medicine · 2010–2019
A researcher in the Science corpus: 6 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Cardiology and Cardiovascular Medicine — 8 citations into it
Whom Gunnar Hartvigsen trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- John Allen (in Biomedical Engineering)
Papers from Gunnar Hartvigsen's perspective
Ordered by how strongly the researchers Gunnar Hartvigsen trusts endorse each paper. Same corpus, a different order for every researcher.
- Anomaly detection: A survey
- Social Uses of Personal Health Information Within PatientsLikeMe, an Online Patient Community: What Can Happen When Patients Have Access to One Another’s Data (Journal of Medical Internet Research)
- Accelerometers and pedometers: methodology and clinical application (Current opinion in clinical nutrition and metabolic care)
- Personal health records: definitions, benefits, and strategies for overcoming barriers to adoption. (JAMIA Journal of the American Medical Informatics Association)
- Sharing Health Data for Better Outcomes on PatientsLikeMe (Journal of Medical Internet Research)
- Evaluating Real-Time Anomaly Detection Algorithms -- The Numenta Anomaly Benchmark (International Conference on Machine Learning and Applications)
- Effects of Intensive Blood-Pressure Control in Type 2 Diabetes Mellitus (New England Journal of Medicine)
- The global economic burden of diabetes in adults aged 20-79 years: a cost-of-illness study. (The Lancet Diabetes and Endocrinology)
- Behavior Change Techniques Present in Wearable Activity Trackers: A Critical Analysis (JMIR mHealth and uHealth)
- Systematic review of the validity and reliability of consumer-wearable activity trackers (International Journal of Behavioral Nutrition and Physical Activity)
Their papers
- Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes (2019) — 306 citations
- Data-Driven Blood Glucose Pattern Classification and Anomalies Detection: Machine-Learning Applications in Type 1 Diabetes (2019) — 144 citations
- Using Fitness Trackers and Smartwatches to Measure Physical Activity in Research: Analysis of Consumer Wrist-Worn Wearables (2018) — 499 citations
- App Features for Type 1 Diabetes Support and Patient Empowerment: Systematic Literature Review and Benchmark Comparison (2018) — 43 citations
- Features of Mobile Diabetes Applications: Review of the Literature and Analysis of Current Applications Compared Against Evidence-Based Guidelines (2011) — 493 citations
- Secondary Use of EHR: Data Quality Issues and Informatics Opportunities (2010) — 384 citations