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tcTKB: an integrated cardiovascular toxicity knowledge base for targeted cancer drugs.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Targeted cancer drugs are often associated with unexpectedly high cardiovascular (CV) adverse events. Systematic approaches to studying CV events associated with targeted anticancer drugs have high potential for elucidating the complex pathways under...

Assessing the Utility of Automatic Cancer Registry Notifications Data Extraction from Free-Text Pathology Reports.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Cancer Registries record cancer data by reading and interpreting pathology cancer specimen reports. For some Registries this can be a manual process, which is labour and time intensive and subject to errors. A system for automatic extraction of cance...

Automatically Detecting Failures in Natural Language Processing Tools for Online Community Text.

Journal of medical Internet research
BACKGROUND: The prevalence and value of patient-generated health text are increasing, but processing such text remains problematic. Although existing biomedical natural language processing (NLP) tools are appealing, most were developed to process cli...

Natural language processing as an alternative to manual reporting of colonoscopy quality metrics.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: The adenoma detection rate (ADR) is a quality metric tied to interval colon cancer occurrence. However, manual extraction of data to calculate and track the ADR in clinical practice is labor-intensive. To overcome this difficulty...

Clustering high throughput biological data with B-MST, a minimum spanning tree based heuristic.

Computers in biology and medicine
To address important challenges in bioinformatics, high throughput data technologies are needed to interpret biological data efficiently and reliably. Clustering is widely used as a first step to interpreting high dimensional biological data, such as...

Comparison of Seven Methods for Boolean Factor Analysis and Their Evaluation by Information Gain.

IEEE transactions on neural networks and learning systems
An usual task in large data set analysis is searching for an appropriate data representation in a space of fewer dimensions. One of the most efficient methods to solve this task is factor analysis. In this paper, we compare seven methods for Boolean ...

A knowledge-based algorithm for automatic detection of cephalometric landmarks on CBCT images.

International journal of computer assisted radiology and surgery
PURPOSE: Cone-beam computed tomography (CBCT) is now an established component for 3D evaluation and treatment planning of patients with severe malocclusion and craniofacial deformities. Precision landmark plotting on 3D images for cephalometric analy...

Greedy and Linear Ensembles of Machine Learning Methods Outperform Single Approaches for QSPR Regression Problems.

Molecular informatics
The application of Machine Learning to cheminformatics is a large and active field of research, but there exist few papers which discuss whether ensembles of different Machine Learning methods can improve upon the performance of their component metho...

The intelligence of dual simplex method to solve linear fractional fuzzy transportation problem.

Computational intelligence and neuroscience
An approach is presented to solve a fuzzy transportation problem with linear fractional fuzzy objective function. In this proposed approach the fractional fuzzy transportation problem is decomposed into two linear fuzzy transportation problems. The o...

Automatic abstraction of imaging observations with their characteristics from mammography reports.

Journal of the American Medical Informatics Association : JAMIA
BACKGROUND: Radiology reports are usually narrative, unstructured text, a format which hinders the ability to input report contents into decision support systems. In addition, reports often describe multiple lesions, and it is challenging to automati...