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

研究成果: Article査読

4 被引用数 (Scopus)

抄録

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.

本文言語English
ジャーナルIEEE Journal of Biomedical and Health Informatics
DOI
出版ステータスAccepted/In press - 2021

ASJC Scopus subject areas

  • バイオテクノロジー
  • コンピュータ サイエンスの応用
  • 電子工学および電気工学
  • 健康情報管理

フィンガープリント

「AI-Driven Synthetic Biology for Non-Small Cell Lung Cancer Drug Effectiveness-Cost Analysis in Intelligent Assisted Medical Systems」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル