Personalized Tumor Growth Prediction Using Multiscale Modeling


ÜNSAL S., Acar A. C., Itik M., KABATAŞ A., GEDİKLİ Ö., ÖZDEMİR F., ...Daha Fazla

JOURNAL OF BASIC AND CLINICAL HEALTH SCIENCES, cilt.4, sa.3, ss.347-363, 2020 (ESCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 4 Sayı: 3
  • Basım Tarihi: 2020
  • Doi Numarası: 10.30621/jbachs.2020.1245
  • Dergi Adı: JOURNAL OF BASIC AND CLINICAL HEALTH SCIENCES
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.347-363
  • Anahtar Kelimeler: neoplasms, patient-specific modeling, adenocarcinoma of lung, precision medicine, CELLULAR-AUTOMATON MODEL, MATHEMATICAL-MODEL, CANCER-CELLS, CHEMOTAXIS, INVASION, GLUCOSE, HYPOXIA, SIMULATION, DIFFUSION, EVOLUTION
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Purpose: Cancer is one of the most complex phenomena in biology and medicine. Extensive attempts have been made to work around this complexity. In this study, we try to take a selective approach; not modeling each particular facet in detail but rather only the pertinent and essential parts of the tumor system are simulated and followed by optimization, revealing specific traits. This leads us to a pellucid personalized model which is noteworthy as it closely approximates existing experimental results.