Pregled bibliografske jedinice broj: 121968
Active Subgroup Mining: A Case Study in Coronary Heart Disease Risk Group Detection
Active Subgroup Mining: A Case Study in Coronary Heart Disease Risk Group Detection // Artificial intelligence in medicine, 28 (2003), 27-57 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 121968 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Active Subgroup Mining: A Case Study in Coronary Heart Disease Risk Group Detection
Autori
Gamberger, Dragan ; Lavrač, Nada ; Krstačić, Goran
Izvornik
Artificial intelligence in medicine (0933-3657) 28
(2003);
27-57
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
coronary heart disease; active mining; machine learning; subgroup discovery; risk group detection; non-invasive cardiovascular tests
Sažetak
This paper presents an approach to active mining of patient records aimed at discovering patient groups at high risk for coronary heart disease. The approach proposes active expert involvement in the following steps of the knowledge discovery process: data gathering, cleaning and transformation, subgroup discovery, statistical characterization of induced subgroups, their interpretation, and the evaluation of results. As in the discovery and characterization of risk subgroups the main risk factors are made explicit, the proposed methodology has high potential for patient screening and early detection of patient groups at risk for coronary heart disease.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus
- MEDLINE