AI Medical Compendium Topic:
Data Mining

Clear Filters Showing 611 to 620 of 1525 articles

DEEPred: Automated Protein Function Prediction with Multi-task Feed-forward Deep Neural Networks.

Scientific reports
Automated protein function prediction is critical for the annotation of uncharacterized protein sequences, where accurate prediction methods are still required. Recently, deep learning based methods have outperformed conventional algorithms in comput...

BioWordVec, improving biomedical word embeddings with subword information and MeSH.

Scientific data
Distributed word representations have become an essential foundation for biomedical natural language processing (BioNLP), text mining and information retrieval. Word embeddings are traditionally computed at the word level from a large corpus of unlab...

Classification of Patients with Coronary Microvascular Dysfunction.

IEEE/ACM transactions on computational biology and bioinformatics
While coronary microvascular dysfunction (CMD) is a major cause of ischemia, it is very challenging to diagnose due to lack of CMD-specific screening measures. CMD has been identified as one of the five priority areas of investigation in a 2014 Natio...

Recurrent neural networks with segment attention and entity description for relation extraction from clinical texts.

Artificial intelligence in medicine
At present, great progress has been achieved on the relation extraction for clinical texts, but we have noticed that the current models have great drawbacks when dealing with long sentences and multiple entities in a sentence. In this paper, we propo...

Extracting chemical-protein interactions from biomedical literature via granular attention based recurrent neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The extraction of interactions between chemicals and proteins from biomedical literature is important for many biomedical tasks such as drug discovery and precision medicine. In the existing systems, the methods achieving co...

An adverse drug effect mentions extraction method based on weighted online recurrent extreme learning machine.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Automatic extraction of adverse drug effect (ADE) mentions from biomedical texts is a challenging research problem that has attracted significant attention from the pharmacovigilance and biomedical text mining communities. I...

Predicting Academic Performance of Students Using a Hybrid Data Mining Approach.

Journal of medical systems
Data mining offers strong techniques for different sectors involving education. In the education field the research is developing rapidly increasing due to huge number of student's information which can be used to invent valuable pattern pertaining l...

Predicting coronary artery disease: a comparison between two data mining algorithms.

BMC public health
BACKGROUND: Cardiovascular diseases (CADs) are the first leading cause of death across the world. World Health Organization has estimated that morality rate caused by heart diseases will mount to 23 million cases by 2030. Hence, the use of data minin...

To Generate an Ensemble Model for Women Thyroid Prediction Using Data Mining Techniques.

Asian Pacific journal of cancer prevention : APJCP
Objective: The main objective of this paper is to easily identify thyroid symptom for treatment. Methods: In this paper two main techniques are proposed for mining the hidden pattern in the dataset. Ensemble-I and Ensemble- II both are machine learni...

Directional Relationship Between Vitamin D Status and Prediabetes: A New Approach from Artificial Neural Network in a Cohort of Workers with Overweight-Obesity.

Journal of the American College of Nutrition
Despite the increasing literature on the association of diabetes with inflammation, cardiovascular risk, and vitamin D (25(OH)D) concentrations, strong evidence on the direction of causality among these factors is still lacking. This gap could be ad...