Bio-inspired computation approach for tumor growth with spatial randomness analysis of kidney cancer xenograft pathology slides

EAI International Conference on Bio-inspired Information and Communications Technologies (BICT)

Volumn , Issue , 2015, Pages

  Saribudak, Aydin ^a   Dong, Yiyu ^b   Hsieh, James ^b   Uyar, M Ümit ^a  

^a City College of New York   (United States)

^b MEMORIAL SLOAN KETTERING CANCER CENTER   (United States)

Author keywords

Artificial intelligence; Bio inspired computation; Differential evolution; Exponential linear tumor growth model; H E slide; Kidney cancer; Pathology; Spatial pattern analysis

Indexed keywords

ARTIFICIAL INTELLIGENCE; DISEASES; EVOLUTIONARY ALGORITHMS; IMAGE ANALYSIS; ION BEAMS; OPTIMIZATION; PATHOLOGY; POPULATION STATISTICS; RANDOM PROCESSES; SPATIAL VARIABLES MEASUREMENT; TUMORS;

BIO INSPIRED COMPUTATION; DIFFERENTIAL EVOLUTION; KIDNEY CANCER; SPATIAL PATTERN ANALYSIS; TUMOR GROWTH MODELING;

PARAMETER ESTIMATION;

EID: 85052173939     PISSN: None     EISSN: 24116777     Source Type: Conference Proceeding    
DOI: 10.4108/eai.3-12-2015.2262350     Document Type: Conference Paper

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