AIMC Topic: Databases, Factual

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Real-Time Patient-Specific ECG Classification by 1-D Convolutional Neural Networks.

IEEE transactions on bio-medical engineering
GOAL: This paper presents a fast and accurate patient-specific electrocardiogram (ECG) classification and monitoring system.

An Automatic Subject-Adaptable Heartbeat Classifier Based on Multiview Learning.

IEEE journal of biomedical and health informatics
In this paper, a novel subject-adaptable heartbeat classification model is presented, in order to address the significant interperson variations in ECG signals. A multiview learning approach is proposed to automate subject adaptation using a small am...

Robotic distal pancreatectomy versus conventional laparoscopic distal pancreatectomy: a comparative study for short-term outcomes.

Frontiers of medicine
Robotic system has been increasingly used in pancreatectomy. However, the effectiveness of this method remains uncertain. This study compared the surgical outcomes between robot-assisted laparoscopic distal pancreatectomy and conventional laparoscopi...

Machine Learning Techniques for Prediction of Early Childhood Obesity.

Applied clinical informatics
OBJECTIVES: This paper aims to predict childhood obesity after age two, using only data collected prior to the second birthday by a clinical decision support system called CHICA.

Bit-Scalable Deep Hashing With Regularized Similarity Learning for Image Retrieval and Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Extracting informative image features and learning effective approximate hashing functions are two crucial steps in image retrieval. Conventional methods often study these two steps separately, e.g., learning hash functions from a predefined hand-cra...

Fuzzy Modeling to Predict Severely Depressed Left Ventricular Ejection Fraction following Admission to the Intensive Care Unit Using Clinical Physiology.

TheScientificWorldJournal
Left ventricular ejection fraction (LVEF) constitutes an important physiological parameter for the assessment of cardiac function, particularly in the settings of coronary artery disease and heart failure. This study explores the use of routinely and...

Performance comparison of multi-label learning algorithms on clinical data for chronic diseases.

Computers in biology and medicine
We are motivated by the issue of classifying diseases of chronically ill patients to assist physicians in their everyday work. Our goal is to provide a performance comparison of state-of-the-art multi-label learning algorithms for the analysis of mul...

Sample Selection for Training Cascade Detectors.

PloS one
Automatic detection systems usually require large and representative training datasets in order to obtain good detection and false positive rates. Training datasets are such that the positive set has few samples and/or the negative set should represe...

Features identification for automatic burn classification.

Burns : journal of the International Society for Burn Injuries
PURPOSE: In this paper an automatic system to diagnose burn depths based on colour digital photographs is presented.

Proto-object categorisation and local gist vision using low-level spatial features.

Bio Systems
Object categorisation is a research area with significant challenges, especially in conditions with bad lighting, occlusions, different poses and similar objects. This makes systems that rely on precise information unable to perform efficiently, like...