AIMC Topic: Databases, Factual

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Subject-Independent Brain-Computer Interfaces Based on Deep Convolutional Neural Networks.

IEEE transactions on neural networks and learning systems
For a brain-computer interface (BCI) system, a calibration procedure is required for each individual user before he/she can use the BCI. This procedure requires approximately 20-30 min to collect enough data to build a reliable decoder. It is, theref...

Using multi-layer perceptron with Laplacian edge detector for bladder cancer diagnosis.

Artificial intelligence in medicine
In this paper, the urinary bladder cancer diagnostic method which is based on Multi-Layer Perceptron and Laplacian edge detector is presented. The aim of this paper is to investigate the implementation possibility of a simpler method (Multi-Layer Per...

Real-Time Extraction of Important Surgical Phases in Cataract Surgery Videos.

Scientific reports
The present study aimed to conduct a real-time automatic analysis of two important surgical phases, which are continuous curvilinear capsulorrhexis (CCC), nuclear extraction, and three other surgical phases of cataract surgery using artificial intell...

Machine Learning-Based Prediction Models for 30-Day Readmission after Hospitalization for Chronic Obstructive Pulmonary Disease.

COPD
While machine learning approaches can enhance prediction ability, little is known about their ability to predict 30-day readmission after hospitalization for Chronic Obstructive Pulmonary Disease (COPD). We identified patients aged ≥40 years with unp...

Natural language processing of electronic health records is superior to billing codes to identify symptom burden in hemodialysis patients.

Kidney international
Symptoms are common in patients on maintenance hemodialysis but identification is challenging. New informatics approaches including natural language processing (NLP) can be utilized to identify symptoms from narrative clinical documentation. Here we ...

The feasibility of developing biomarkers from peripheral blood mononuclear cell RNAseq data in children with juvenile idiopathic arthritis using machine learning approaches.

Arthritis research & therapy
BACKGROUND: The response to treatment for juvenile idiopathic arthritis (JIA) can be staged using clinical features. However, objective laboratory biomarkers of remission are still lacking. In this study, we used machine learning to predict JIA activ...

Skin cancer diagnosis based on optimized convolutional neural network.

Artificial intelligence in medicine
Early detection of skin cancer is very important and can prevent some skin cancers, such as focal cell carcinoma and melanoma. Although there are several reasons that have bad impacts on the detection precision. Recently, the utilization of image pro...

Artificial plant optimization algorithm to detect heart rate & presence of heart disease using machine learning.

Artificial intelligence in medicine
In today's world, cardiovascular diseases are prevalent becoming the leading cause of death; more than half of the cardiovascular diseases are due to Coronary Heart Disease (CHD) which generates the demand of predicting them timely so that people can...

Artificial intelligence and big data facilitated targeted drug discovery.

Stroke and vascular neurology
Different kinds of biological databases publicly available nowadays provide us a goldmine of multidiscipline big data. The Cancer Genome Atlas is a cancer database including detailed information of many patients with cancer. DrugBank is a database in...

The Clinical Pharmacogenetics Implementation Consortium: 10 Years Later.

Clinical pharmacology and therapeutics
In 2009, the Clinical Pharmacogenetics Implementation Consortium (CPIC, www.cpicpgx.org), a shared project between Pharmacogenomics Knowledge Base (PharmGKB, http://www.pharmgkb.org) and the National Institutes of Health (NIH), was created to provide...