AI Medical Compendium Topic

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Pharmaceutical Preparations

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DeepPurpose: a deep learning library for drug-target interaction prediction.

Bioinformatics (Oxford, England)
SUMMARY: Accurate prediction of drug-target interactions (DTI) is crucial for drug discovery. Recently, deep learning (DL) models for show promising performance for DTI prediction. However, these models can be difficult to use for both computer scien...

Towards Equitable AI Interventions for People Who Use Drugs: Key Areas That Require Ethical Investment.

Journal of addiction medicine
There has been growing investment in artificial intelligence (AI) interventions to combat the opioid-driven overdose epidemic plaguing North America. Although the evidence for the use of technology and AI in medicine is mounting, there are a number o...

Building longitudinal medication dose data using medication information extracted from clinical notes in electronic health records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To develop an algorithm for building longitudinal medication dose datasets using information extracted from clinical notes in electronic health records (EHRs).

Artificial Intelligence in Pharmaceutical Field - A Critical Review.

Current drug delivery
Artificial intelligence is an emerging sector in almost all fields. It is not confined only to a particular category and can be used in various fields like research, technology, and health. AI mainly concentrates on how computers analyze data and mim...

Artificial Intelligence, Big Data and Machine Learning Approaches in Precision Medicine & Drug Discovery.

Current drug targets
Artificial Intelligence revolutionizes the drug development process that can quickly identify potential biologically active compounds from millions of candidate within a short period. The present review is an overview based on some applications of Ma...

Deep Learning in Drug Target Interaction Prediction: Current and Future Perspectives.

Current medicinal chemistry
Drug-target Interactions (DTIs) prediction plays a central role in drug discovery. Computational methods in DTIs prediction have gained more attention because carrying out in vitro and in vivo experiments on a large scale is costly and time-consuming...

Application of Machine Learning Techniques to Predict Binding Affinity for Drug Targets: A Study of Cyclin-Dependent Kinase 2.

Current medicinal chemistry
BACKGROUND: The elucidation of the structure of cyclin-dependent kinase 2 (CDK2) made it possible to develop targeted scoring functions for virtual screening aimed to identify new inhibitors for this enzyme. CDK2 is a protein target for the developme...

An omics perspective on drug target discovery platforms.

Briefings in bioinformatics
The drug discovery process starts with identification of a disease-modifying target. This critical step traditionally begins with manual investigation of scientific literature and biomedical databases to gather evidence linking molecular target to di...

Rapid prediction of drug inhibition under heat stress: single-photon imaging combined with a convolutional neural network.

Nanoscale
A method of predicting cellular drug inhibition due to heat stress is presented. Black phosphorus nanosheets are used as photothermal agents to induce stress granule formation in tumor cells. The addition of different drugs induces different thermal ...