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Publication QA: Using Artificial Intelligence to Predict Drug Interactions and More Effective Treatments for Tuberculosis

Sherman, Sriram Chandrasekaran Published in mBio: October 2019 Read the publication on mBio The Sherman lab is using experimental and computational systems biology tools to understand how the pathogen Mycobacterium tuberculosis (MTB) responds to stresses encountered during infection and to drug exposure.

We are studying this pathogen in part to devise new treatment strategies for the disease that it causes: tuberculosis (TB), which is the world’s deadliest infectious disease, killing approximately 2 million people each year.

Third, the input data needed to calculate predictions for new drugs are highly modular, requiring only the bacterial response for the new individual drug to predict interactions between all possible combinations with previously profiled drugs.

We are also working with Dr. Rafael Hernandez (CGIDR faculty) to extend the underlying modeling approach to be able to predict efficacy for drug regimens treating other recalcitrant pathogens, including Mycobacteria absessus, a pathogen related to MTB that commonly infects cystic fibrosis patients in the U.S. Seattle Children’s CGIDR contributing authors:

Artificial Intelligence in Cancer - Baishideng Publishing Group

The research interests focus on biotherapy of cancer, tumor microenvironment, statistical genetics, biomarker research, and deep learning of medical imaging.

Ma Lao serves as editor in chief of special issues of magazines such as Frontiers in Pharmacology, Contrast media and molecular imaging and some magazines.

The research interests focus on biotherapy of cancer, tumor microenvironment, statistical genetics, biomarker research, and deep learning of medical imaging.

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Artificial Intelligence in 2020

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Mario Mariniello explains ‘The Age of Artificial Intelligence’

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Inside Knowhere: News Written by Artificial Intelligence | Inverse

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15 BEST Books On A.I.

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CEDIA 2016: Josh.ai Is An Artificial Intelligence System That Works with Current IP Enabled System

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Kate Crawford | AI Now: Social and Political Questions for Artificial Intelligence

The impact of early AI systems is already being felt, bringing with it challenges and opportunities, and laying the foundation on which future advances in AI will ...

Prof. Brian Cox - Machine Learning & Artificial Intelligence - Royal Society

Produced by the Royal Society, more info can be found at Brian Edward Cox is physicist who ..

"Town Hall on A.I., Machine Learning, and More," with Peter Norvig

Title: Town Hall with Peter Norvig on A.I., Machine Learning, and More Time: 12:00 PM EST on December 8, 2016 Duration: 1 hour, 2 minutes SUMMARY: Peter ...