Data-driven approach of Cusum algorithm in temporal aberrant event detection using interactive web applications
Bibliographic Data
| ID | 8897804 |
|---|---|
| Authors | Ye Li (0000-0002-5043-9797, Public Health Ontario, corresponding author), Michael Whelan (0000-0003-2858-5496, Public Health Ontario), Leigh Hobbs (Public Health Ontario), Wen Qi Fan (Public Health Ontario), Cecilia Fung (Public Health Ontario), Kenny K Wong (Public Health Ontario), Kenny Wong, Alex Marchand‐Austin (0000-0001-5932-2037, Public Health Ontario), Alex Marchand-Austin, Tina Badiani (Public Health Ontario), Ian Johnson (0000-0002-9476-6220, University of Toronto) |
| Year | 2016 |
| Volume | 107 |
| Issue | 1 |
| Pages | e9-e15 |
| Publication date | 2016-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Canadian Journal of Public Health (JOURNAL) |
| Journal identifiers | ISSN: 0008-4263 • E-ISSN: 1920-7476 |
| Publisher | Springer Science+Business Media (PUBLISHER • DE) |
| DOI | 10.17269/cjph.107.5228 |
| PMID | 27348117 |
| OpenAlex | W2460090577 |
| Language | EN |
| References cited | 6 |
Algorithm · CUSUM · Data mining · Event (particle physics · Statistics · Temporal database · Advanced Statistical Process Monitoring · Anomaly Detection Techniques and Applications · Artificial Intelligence · Computer Science · Mathematics · Time Series Analysis and Forecasting
| Highly cited | No |
|---|