AI Medical Compendium Topic

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Pharmaceutical Preparations

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Artificial Intelligence Assisted Fabrication of 3D, 4D and 5D Printed Formulations or Devices for Drug Delivery.

Current drug delivery
5D & 4D printings are an advanced version of 3D printing class and are one of the most revolutionary and powerful fabrication methods used for preparing innovative structures and solid substances using precise additive manufacturing technology. It ca...

Biological activities of drug inactive ingredients.

Briefings in bioinformatics
In a drug formulation (DFM), the major components by mass are not Active Pharmaceutical Ingredient (API) but rather Drug Inactive Ingredients (DIGs). DIGs can reach much higher concentrations than that achieved by API, which raises great concerns abo...

SuperPred 3.0: drug classification and target prediction-a machine learning approach.

Nucleic acids research
Since the last published update in 2014, the SuperPred webserver has been continuously developed to offer state-of-the-art models for drug classification according to ATC classes and target prediction. For the first time, a thoroughly filtered ATC da...

BioDKG-DDI: predicting drug-drug interactions based on drug knowledge graph fusing biochemical information.

Briefings in functional genomics
The way of co-administration of drugs is a sensible strategy for treating complex diseases efficiently. Because of existing massive unknown interactions among drugs, predicting potential adverse drug-drug interactions (DDIs) accurately is promotive t...

Knowledge-based BERT: a method to extract molecular features like computational chemists.

Briefings in bioinformatics
Molecular property prediction models based on machine learning algorithms have become important tools to triage unpromising lead molecules in the early stages of drug discovery. Compared with the mainstream descriptor- and graph-based methods for mol...

Prediction of disease-associated nsSNPs by integrating multi-scale ResNet models with deep feature fusion.

Briefings in bioinformatics
More than 6000 human diseases have been recorded to be caused by non-synonymous single nucleotide polymorphisms (nsSNPs). Rapid and accurate prediction of pathogenic nsSNPs can improve our understanding of the principle and design of new drugs, which...

HINGRL: predicting drug-disease associations with graph representation learning on heterogeneous information networks.

Briefings in bioinformatics
Identifying new indications for drugs plays an essential role at many phases of drug research and development. Computational methods are regarded as an effective way to associate drugs with new indications. However, most of them complete their tasks ...

Trial Approach for Biomedical Products: A Regulatory Perspective.

Combinatorial chemistry & high throughput screening
The modern pharmaceutical industry is transitioning from traditional methods to advanced technologies like artificial intelligence. In the current scenario, continuous efforts are being made to incorporate computational modeling and simulation in dru...

De novo Prediction of Cell-Drug Sensitivities Using Deep Learning-based Graph Regularized Matrix Factorization.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Application of artificial intelligence (AI) in precision oncology typically involves predicting whether the cancer cells of a patient (previously unseen by AI models) will respond to any of a set of existing anticancer drugs, based on responses of pr...