Advancements in artificial intelligence and machine learning in revolutionising biomarker discovery

被引:1
|
作者
Raikar, Gokuldas Sarvesh [1 ]
Raikar, Amisha Sarvesh [2 ]
Somnache, Sandesh Narayan [2 ]
机构
[1] Manipal Inst Technol, Dept Comp Sci Artificial Intelligence, Bengaluru, Karnataka, India
[2] PES Rajaram & Tarabai Bandekar Coll Pharm, Dept Pharmaceut, Farmagudi Ponda, Goa, India
关键词
Biomarkers. Artificial Intelligence. Machine Learning. Multi-omics. Omics; METABOLOMICS; EXTRACTION; EXPRESSION; PREDICTION; RESISTANCE; DATABASE; GENES; INDEX; RISK;
D O I
10.1590/s2175-97902023e23146
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
The article explores the significance of biomarkers in clinical research and the advantages of utilizing artificial intelligence (AI) and machine learning (ML) in the discovery process. Biomarkers provide a more comprehensive understanding of disease progression and response to therapy compared to traditional indicators. AI and ML offer a new approach to biomarker discovery, leveraging large amounts of data to identify patterns and optimize existing biomarkers. Additionally, the article touches on the emergence of digital biomarkers, which use technology to assess an individual's physiological and behavioural states, and the importance of properly processing omics and multi-omics data for efficient handling by computer systems. However, the article acknowledges the challenges posed by AI/ML in the identification of biomarkers, including potential biases in the data and the need for diversity in data representation. To address these challenges, the article suggests the importance of regulation and diversity in the development of AI/ML algorithms.
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页数:26
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