Author

T. J. Anastasio

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Pharmacology & Toxicology· 2

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Assay:clinical cohort / trial· 2 Research Focus:drug response / drug discovery· 2 Organism:human· 2 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Activity by Year

2018-2020 · peak 1/yr

2 papers

Recent·Most cited

Pharmacology & ToxicologybioRxivApr 28, 2020

Predicting the potency of anti-Alzheimer drug combinations using machine learning

T. J. Anastasio

This study uses machine learning to predict effective anti-Alzheimer drug combinations by analyzing data from two AD databases.

DOI 10.3390/pr9020264

humanclinical cohort / trial

𝕏 PostBluesky

Pharmacology & ToxicologybioRxivOct 8, 2018

Exploring the Correlation between the Cognitive Benefits of Drug Combinations in a Clinical Alzheimer Disease Database and the Efficacies of the Same Drug Combinations Predicted from a Computational Model

T. J. Anastasio

The paper identifies drug combinations with potential therapeutic benefits for Alzheimer's disease by correlating clinical data with computational model predictions.

DOI 10.3233/jad-190144

humanclinical cohort / trial

𝕏 PostBluesky