AI-Driven Synthetic Biology for Non-Small Cell Lung Cancer Drug Effectiveness-Cost Analysis in Intelligent Assisted Medical Systems

Liu Chang, Jia Wu, Nour Moustafa, Ali Kashif Bashir, Keping Yu

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

According to statistics, in the 185 countries' 36 types of cancer, the morbidity and mortality of lung cancer take the first place, and non-small cell lung cancer (NSCLC) accounts for 85% of lung cancer [1-2]. Significantly in many developing countries, limited medical resources and excess population seriously affect the diagnosis and treatment of lung cancer patients. The 21st century is an era of life medicine, big data, and information technology. Synthetic biology is known as the driving force of natural product innovation and research in this era. Based on the research of NSCLC targeted drugs, through the cross-fusion of synthetic biology and artificial intelligence, using the idea of bioengineering, we construct an artificial intelligence assisted medical system and propose a drug selection framework for the personalized selection of NSCLC patients. Under the premise of ensuring the efficacy, considering the economic cost of targeted drugs as an auxiliary decision-making factor, the system predicts the drug effectiveness-cost then. The experiment shows that our method can rely on the provided clinical data to screen drug treatment programs suitable for the patient's conditions and assist doctors in making an efficient diagnosis.

Original languageEnglish
JournalIEEE Journal of Biomedical and Health Informatics
DOIs
Publication statusAccepted/In press - 2021

Keywords

  • artificial intelligence medical system
  • Bioinformatics
  • Costs
  • drug effectiveness-cost analysis
  • Drugs
  • Lung cancer
  • Medical diagnostic imaging
  • non-small cell lung cancer (NSCLC)
  • Synthetic biology
  • synthetic biology
  • targeted drug therapy
  • Tumors

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Health Information Management

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