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Drug Therapy

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The Application of Machine Learning Techniques in Clinical Drug Therapy.

Current computer-aided drug design
INTRODUCTION: The development of a novel drug is an extremely complicated process that includes the target identification, design and manufacture, and proper therapy of the novel drug, as well as drug dose selection, drug efficacy evaluation, and adv...

Drug Repositioning by Integrating Known Disease-Gene and Drug-Target Associations in a Semi-supervised Learning Model.

Acta biotheoretica
Computational drug repositioning has been proven as a promising and efficient strategy for discovering new uses from existing drugs. To achieve this goal, a number of computational methods have been proposed, which are based on different data sources...

Automated ontology generation framework powered by linked biomedical ontologies for disease-drug domain.

Computer methods and programs in biomedicine
OBJECTIVE AND BACKGROUND: The exponential growth of the unstructured data available in biomedical literature, and Electronic Health Record (EHR), requires powerful novel technologies and architectures to unlock the information hidden in the unstructu...

Methodological variations in lagged regression for detecting physiologic drug effects in EHR data.

Journal of biomedical informatics
We studied how lagged linear regression can be used to detect the physiologic effects of drugs from data in the electronic health record (EHR). We systematically examined the effect of methodological variations ((i) time series construction, (ii) tem...

Enhancing Seasonal Influenza Surveillance: Topic Analysis of Widely Used Medicinal Drugs Using Twitter Data.

Journal of medical Internet research
BACKGROUND: Uptake of medicinal drugs (preventive or treatment) is among the approaches used to control disease outbreaks, and therefore, it is of vital importance to be aware of the counts or frequencies of most commonly used drugs and trending topi...

Network mirroring for drug repositioning.

BMC medical informatics and decision making
BACKGROUND: Although drug discoveries can provide meaningful insights and significant enhancements in pharmaceutical field, the longevity and cost that it takes can be extensive where the success rate is low. In order to circumvent the problem, there...

The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology.

Oncotarget
Recent advances in deep learning and specifically in generative adversarial networks have demonstrated surprising results in generating new images and videos upon request even using natural language as input. In this paper we present the first applic...

Learning disease relationships from clinical drug trials.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Our objective is to test the limits of the assumption that better learning from data in medicine requires more granular data. We hypothesize that clinical trial metadata contains latent scientific, clinical, and regulatory expert knowledge...

Magnetic nanoparticles and nanocomposites for remote controlled therapies.

Journal of controlled release : official journal of the Controlled Release Society
This review highlights the state-of-the-art in the application of magnetic nanoparticles (MNPs) and their composites for remote controlled therapies. Novel macro- to nano-scale systems that utilize remote controlled drug release due to actuation of M...

Oncotherapy: A System for Requesting Chemotherapy Protocols.

Studies in health technology and informatics
A clinical decision support system is able to provide oncologists with suitable treatment options at the moment of decision making regarding which chemotherapy protocol is the best to apply to a particular oncological case. The National Cancer Instit...