OBJECTIVE: We study the performance of machine learning (ML) methods, including neural networks (NNs), to extract mutational test results from pathology reports collected by cancer registries. Given the lack of hand-labeled datasets for mutational te...
The characterization of antimicrobial resistance genes from high-throughput sequencing data has become foundational in public health research and regulation. This requires mapping sequence reads to databases of known antimicrobial resistance genes to...
Neural networks : the official journal of the International Neural Network Society
Aug 1, 2019
Robust Principal Component Analysis (RPCA) is a powerful tool in machine learning and data mining problems. However, in many real-world applications, RPCA is unable to well encode the intrinsic geometric structure of data, thereby failing to obtain t...
A major challenge in cancer treatment is predicting the clinical response to anti-cancer drugs on a personalized basis. The success of such a task largely depends on the ability to develop computational resources that integrate big "omic" data into e...
Significant progress has been made in applying deep learning on natural language processing tasks recently. However, deep learning models typically require a large amount of annotated training data while often only small labeled datasets are availabl...
BACKGROUND: Diabetes mellitus (DM) is a metabolic disorder that causes abnormal blood glucose (BG) regulation that might result in short and long-term health complications and even death if not properly managed. Currently, there is no cure for diabet...
Computer methods and programs in biomedicine
Jul 24, 2019
BACKGROUND AND OBJECTIVE: Coronary artery disease (CAD) is one of the commonest diseases around the world. An early and accurate diagnosis of CAD allows a timely administration of appropriate treatment and helps to reduce the mortality. Herein, we de...
The early and accurately detection of brucellosis incidence change is of great importance for implementing brucellosis prevention strategic health planning. The present study investigated and compared the performance of the three data mining techniqu...
Computational intelligence and neuroscience
Jul 14, 2019
Relation extraction is the underlying critical task of textual understanding. However, the existing methods currently have defects in instance selection and lack background knowledge for entity recognition. In this paper, we propose a knowledge-based...
Neural networks : the official journal of the International Neural Network Society
Jul 8, 2019
Text classification has been attracting increasing attention with the growth of textual data created on the Internet. Great progress has been made by deep neural networks for domains where a large amount of labeled training data is available. However...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.