期刊
PERSONALIZED MEDICINE
卷 12, 期 4, 页码 371-387出版社
FUTURE MEDICINE LTD
DOI: 10.2217/PME.15.5
关键词
cancer biomarkers; genomics; machine learning; personalized medicine; predictive classification models; sequencing
资金
- Department of Biotechnology (DBT, India) [BT/BI/25/001/2006]
- University Grants Commission (UGC, India)
The patterns identified from the systematically collected molecular profiles of patient tumor samples, along with clinical metadata, can assist personalized treatments for effective management of cancer patients with similar molecular subtypes. There is an unmet need to develop computational algorithms for cancer diagnosis, prognosis and therapeutics that can identify complex patterns and help in classifications based on plethora of emerging cancer research outcomes in public domain. Machine learning, a branch of artificial intelligence, holds a great potential for pattern recognition in cryptic cancer datasets, as evident from recent literature survey. In this review, we focus on the current status of machine learning applications in cancer research, highlighting trends and analyzing major achievements, roadblocks and challenges toward its implementation in clinics.
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