AIMC Topic: Pattern Recognition, Automated
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Machine learning to predict 30-day quality-adjusted survival in critically ill patients with cancer.
Journal of critical care
Nov 2, 2019
PURPOSE: To develop and compare the predictive performance of machine-learning algorithms to estimate the risk of quality-adjusted life year (QALY) lower than or equal to 30 days (30-day QALY).
Middle Aged
Prospective Studies
Brazil
Neoplasms
Prognosis
Quality of Life
Critical Illness
Adult
Sensitivity and Specificity
Intensive Care Units
Male
Female
Probability
Hospitalization
Pattern Recognition, Automated
Humans
Aged
False Positive Reactions
Machine Learning
Hospitals, Public
Algorithms
ROC Curve
Decision Trees
Area Under Curve
Signal Processing, Computer-Assisted
Urine Sediment Recognition Method Based on Multi-View Deep Residual Learning in Microscopic Image.
Journal of medical systems
Oct 23, 2019
Urine sediment recognition is attracting growing interest in the field of computer vision. A multi-view urine cell recognition method based on multi-view deep residual learning is proposed to solve some existing problems, such as multi-view cell gray...
Multi-label zero-shot human action recognition via joint latent ranking embedding.
Neural networks : the official journal of the International Neural Network Society
Oct 21, 2019
Human action recognition is one of the most challenging tasks in computer vision. Most of the existing works in human action recognition are limited to single-label classification. A real-world video stream, however, often contains multiple human act...
Test-retest reliability of spatial patterns from resting-state functional MRI using the restricted Boltzmann machine and hierarchically organized spatial patterns from the deep belief network.
Journal of neuroscience methods
Oct 15, 2019
BACKGROUND: Restricted Boltzmann machines (RBMs), including greedy layer-wise trained RBMs as part of a deep belief network (DBN), have the ability to identify spatial patterns (SPs; functional networks) in resting-state fMRI (rfMRI) data. However, t...
Large-Truck Safety Warning System Based on Lightweight SSD Model.
Computational intelligence and neuroscience
Oct 13, 2019
Transportation is an important link in the mining process, and large trucks are one of the important tools for mine transportation. Due to their large size and small driving position, large trucks have a blind spot, which is a hidden danger to the sa...
Development of a Wearable Electrical Impedance Tomographic Sensor for Gesture Recognition With Machine Learning.
IEEE journal of biomedical and health informatics
Oct 4, 2019
A wearable electrical impedance tomographic (wEIT) sensor with 8 electrodes is developed to realize gesture recognition with machine learning algorithms. To optimize the wEIT sensor, gesture recognition rates are compared by using a series of electro...
Defining and distinguishing infant behavioral states using acoustic cry analysis: is colic painful?
Pediatric research
Oct 4, 2019
BACKGROUND: To characterize acoustic features of an infant's cry and use machine learning to provide an objective measurement of behavioral state in a cry-translator. To apply the cry-translation algorithm to colic hypothesizing that these cries soun...
IDRiD: Diabetic Retinopathy - Segmentation and Grading Challenge.
Medical image analysis
Oct 3, 2019
Diabetic Retinopathy (DR) is the most common cause of avoidable vision loss, predominantly affecting the working-age population across the globe. Screening for DR, coupled with timely consultation and treatment, is a globally trusted policy to avoid ...
CNN-based diagnosis models for canine ulcerative keratitis.
Scientific reports
Oct 2, 2019
The purpose of this methodological study was to develop a convolutional neural network (CNN), which is a recently developed deep-learning-based image recognition method, to determine corneal ulcer severity in dogs. The CNN model was trained with imag...
An Ontology-Based Artificial Intelligence Model for Medicine Side-Effect Prediction: Taking Traditional Chinese Medicine as an Example.
Computational and mathematical methods in medicine
Oct 1, 2019
In this work, an ontology-based model for AI-assisted medicine side-effect (SE) prediction is developed, where three main components, including the drug model, the treatment model, and the AI-assisted prediction model, of the proposed model are prese...
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