Application of Techniques Based on Artificial Intelligence for Predicting the Consumption of Drugs and Substances. A Systematic Mapping Review

Torres-Carrión, Pablo; Reátegui, Ruth; Valdiviezo, Priscila; Bustamante, Byron; Vaca, Silvia

doi:10.1007/978-3-030-42520-3_4

Cited by 1 publication

(1 citation statement)

References 19 publications

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“…PROFILER is the automated workflow designed by scientists for the identification of the perfect targets which possess highest activity of binding with the targeted molecule [36]. It integrates with two-structural based approaches which include protein ligand binding pharmacophores search and docking and another four structural based approaches which include vector regression affinity based prediction, SVM binary classifications, three dimensional similarity search function and neighboring affinity prediction [37]. In the virtual screen of structure-based prediction, RF score has been found and applied subsequently for the prediction if accurate targets.…”

Section: Role Of Ai In Drug Identificationmentioning

confidence: 99%

Role of Artificial Intelligence and Machine Learning in Bioinformatics: Drug Discovery and Drug Repurposing

Quazi¹

2021

Preprint

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Artificial intelligence AI or machine learning has proven to be a potential activity in the health and biomedical sciences. Previous research it has found that AI can learn new data and transform it into the useful knowledge. In the field of pharmacology, the aim is to design more efficient and novel vaccines using this method which are also cost effective. The underlying fact is to predict the molecular mechanism and structure for increased likelihood of developing new drugs. Clinical, electronic and high resolution imaging datasets can be used as inputs to aid the drug development niche. Moreover, the use of comprehensive target activity has been performed for repurposing a drug molecule by extending target profiles of drugs which also include off targets with therapeutic potential providing a new indication.

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Section: Role Of Ai In Drug Identificationmentioning

confidence: 99%

Role of Artificial Intelligence and Machine Learning in Bioinformatics: Drug Discovery and Drug Repurposing

Quazi¹

2021

Preprint

View full text Add to dashboard Cite

show abstract

Application of Techniques Based on Artificial Intelligence for Predicting the Consumption of Drugs and Substances. A Systematic Mapping Review

Cited by 1 publication

References 19 publications

Role of Artificial Intelligence and Machine Learning in Bioinformatics: Drug Discovery and Drug Repurposing

Role of Artificial Intelligence and Machine Learning in Bioinformatics: Drug Discovery and Drug Repurposing

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