AI Medical Compendium Topic

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Drug Resistance, Neoplasm

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Deep learning for drug response prediction in cancer.

Briefings in bioinformatics
Predicting the sensitivity of tumors to specific anti-cancer treatments is a challenge of paramount importance for precision medicine. Machine learning(ML) algorithms can be trained on high-throughput screening data to develop models that are able to...

DeepDSC: A Deep Learning Method to Predict Drug Sensitivity of Cancer Cell Lines.

IEEE/ACM transactions on computational biology and bioinformatics
High-throughput screening technologies have provided a large amount of drug sensitivity data for a panel of cancer cell lines and hundreds of compounds. Computational approaches to analyzing these data can benefit anticancer therapeutics by identifyi...

The emerging roles of artificial intelligence in cancer drug development and precision therapy.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
Artificial intelligence (AI) has strong logical reasoning ability and independent learning ability, which can simulate the thinking process of the human brain. AI technologies such as machine learning can profoundly optimize the existing mode of anti...

Convolutional Neural Network Can Recognize Drug Resistance of Single Cancer Cells.

International journal of molecular sciences
It is known that single or isolated tumor cells enter cancer patients' circulatory systems. These circulating tumor cells (CTCs) are thought to be an effective tool for diagnosing cancer malignancy. However, handling CTC samples and evaluating CTC se...

RefDNN: a reference drug based neural network for more accurate prediction of anticancer drug resistance.

Scientific reports
Cancer is one of the most difficult diseases to treat owing to the drug resistance of tumour cells. Recent studies have revealed that drug responses are closely associated with genomic alterations in cancer cells. Numerous state-of-the-art machine le...

Ensembled machine learning framework for drug sensitivity prediction.

IET systems biology
Drug sensitivity prediction is one of the critical tasks involved in drug designing and discovery. Recently several online databases and consortiums have contributed to providing open access to pharmacogenomic data. These databases have helped in dev...

Identification of leukemia stem cell expression signatures through Monte Carlo feature selection strategy and support vector machine.

Cancer gene therapy
Acute myeloid leukemia (AML) is a type of blood cancer characterized by the rapid growth of immature white blood cells from the bone marrow. Therapy resistance resulting from the persistence of leukemia stem cells (LSCs) are found in numerous patient...

A Deep Learning Framework for Predicting Response to Therapy in Cancer.

Cell reports
A major challenge in cancer treatment is predicting clinical response to anti-cancer drugs on a personalized basis. Using a pharmacogenomics database of 1,001 cancer cell lines, we trained deep neural networks for prediction of drug response and asse...

Network as a Biomarker: A Novel Network-Based Sparse Bayesian Machine for Pathway-Driven Drug Response Prediction.

Genes
With the advances in different biological networks including gene regulation, gene co-expression, protein-protein interaction networks, and advanced approaches for network reconstruction, analysis, and interpretation, it is possible to discover relia...