A fuzzy measurement-based assessment of breast cancer prognostic markers

Proceedings of the IEEE/EMBS Region 8 International Conference on Information Technology Applications in Biomedicine, ITAB

Volumn , Issue , 2000, Pages 174-178

  Seker, H ^a   Odetayo, M ^a   Petrovic, D ^a   Naguib, R N G ^a   Bartoli, C ^a   Alasio, L ^a   Lakshmi, M S ^a   Sherbet, G V ^a  

^a Institute for Clean Growth and Future Mobility   (United Kingdom)

Author keywords

Artificial intelligence; Oncology; Predictive analysis; Soft feature subset selection; Survival analysis

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DNA; FEATURE EXTRACTION; FUZZY SETS; HISTOLOGY; PATIENT TREATMENT; TUMORS;

BREAST CANCER; PROGNOSTICS; SOFT FEATURE SUBSET SELECTION;

ONCOLOGY;

EID: 0034450238     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (4)

1. DNA ploidy and cell cycle distribution of breast cancer aspirate cells measured by image cytometry and analysed by artificial neural networks for their prognostic significance
2. Ranking prostate cancer prognostic markers using a fuzzy K-Nearest neighbour algorithm
3. A soft measurement technique for searching significant subsets of prostate cancer prognostic markers
4. A fuzzy K-nearest neighbour algorithm