AIMC Topic: Clinical Trials as Topic

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Automated identification of molecular effects of drugs (AIMED).

Journal of the American Medical Informatics Association : JAMIA
INTRODUCTION: Genomic profiling information is frequently available to oncologists, enabling targeted cancer therapy. Because clinically relevant information is rapidly emerging in the literature and elsewhere, there is a need for informatics technol...

Extracting genetic alteration information for personalized cancer therapy from ClinicalTrials.gov.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Clinical trials investigating drugs that target specific genetic alterations in tumors are important for promoting personalized cancer therapy. The goal of this project is to create a knowledge base of cancer treatment trials with annotati...

canSAR: an updated cancer research and drug discovery knowledgebase.

Nucleic acids research
canSAR (http://cansar.icr.ac.uk) is a publicly available, multidisciplinary, cancer-focused knowledgebase developed to support cancer translational research and drug discovery. canSAR integrates genomic, protein, pharmacological, drug and chemical da...

Textual inference for eligibility criteria resolution in clinical trials.

Journal of biomedical informatics
Clinical trials are essential for determining whether new interventions are effective. In order to determine the eligibility of patients to enroll into these trials, clinical trial coordinators often perform a manual review of clinical notes in the e...

RobotReviewer: evaluation of a system for automatically assessing bias in clinical trials.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To develop and evaluate RobotReviewer, a machine learning (ML) system that automatically assesses bias in clinical trials. From a (PDF-formatted) trial report, the system should determine risks of bias for the domains defined by the Cochra...

Increasing the efficiency of trial-patient matching: automated clinical trial eligibility pre-screening for pediatric oncology patients.

BMC medical informatics and decision making
BACKGROUND: Manual eligibility screening (ES) for a clinical trial typically requires a labor-intensive review of patient records that utilizes many resources. Leveraging state-of-the-art natural language processing (NLP) and information extraction (...

Knowledge bases, clinical decision support systems, and rapid learning in oncology.

Journal of oncology practice
One of the most important benefits of health information technology is to assist the cognitive process of the human mind in the face of vast amounts of health data, limited time for decision making, and the complexity of the patient with cancer. Clin...

Aggregator: a machine learning approach to identifying MEDLINE articles that derive from the same underlying clinical trial.

Methods (San Diego, Calif.)
OBJECTIVE: It is important to identify separate publications that report outcomes from the same underlying clinical trial, in order to avoid over-counting these as independent pieces of evidence.

Automated clinical trial eligibility prescreening: increasing the efficiency of patient identification for clinical trials in the emergency department.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: (1) To develop an automated eligibility screening (ES) approach for clinical trials in an urban tertiary care pediatric emergency department (ED); (2) to assess the effectiveness of natural language processing (NLP), information extractio...

Comparative effectiveness of anti-seizure medications in emulated trials using medical informatics.

Brain : a journal of neurology
Anti-seizure medications (ASMs) are often prescribed using a trial-and-error approach with a similar sequence for many patients. Comparative effectiveness data beyond the first ASM prescription are limited. Artificial intelligence can automatically e...