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Databases, Factual
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TISNet-Enhanced Fully Convolutional Network with Encoder-Decoder Structure for Tongue Image Segmentation in Traditional Chinese Medicine.
Computational and mathematical methods in medicine
Aug 7, 2020
Extracting the tongue body accurately from a digital tongue image is a challenge for automated tongue diagnoses, as the blurred edge of the tongue body, interference of pathological details, and the huge difference in the size and shape of the tongue...
Twin minimax probability machine for pattern classification.
Neural networks : the official journal of the International Neural Network Society
Aug 1, 2020
We propose a new distribution-free Bayes optimal classifier, called the twin minimax probability machine (TWMPM), which combines the benefits of both minimax probability machine(MPM) and twin support vector machine (TWSVM). TWMPM tries to construct t...
Research and Verification of Convolutional Neural Network Lightweight in BCI.
Computational and mathematical methods in medicine
Aug 1, 2020
With the increasing of depth and complexity of the convolutional neural network, parameter dimensionality and volume of computing have greatly restricted its applications. Based on the SqueezeNet network structure, this study introduces a block convo...
A Comparative Analysis of Visual Encoding Models Based on Classification and Segmentation Task-Driven CNNs.
Computational and mathematical methods in medicine
Aug 1, 2020
Nowadays, visual encoding models use convolution neural networks (CNNs) with outstanding performance in computer vision to simulate the process of human information processing. However, the prediction performances of encoding models will have differe...
A Simple Method to Train the AI Diagnosis Model of Pulmonary Nodules.
Computational and mathematical methods in medicine
Aug 1, 2020
BACKGROUND: The differential diagnosis of subcentimetre lung nodules with a diameter of less than 1 cm has always been one of the problems of imaging doctors and thoracic surgeons. We plan to create a deep learning model for the diagnosis of pulmonar...
Lung Neoplasms
Adenocarcinoma of Lung
Carcinoma, Non-Small-Cell Lung
Artificial Intelligence
Multiple Pulmonary Nodules
Databases, Factual
Diagnosis, Differential
Humans
Solitary Pulmonary Nodule
Tomography, X-Ray Computed
Radiographic Image Interpretation, Computer-Assisted
Deep Learning
Expert Systems
Expert Testimony
A Novel Hybrid Model Based on a Feedforward Neural Network and One Step Secant Algorithm for Prediction of Load-Bearing Capacity of Rectangular Concrete-Filled Steel Tube Columns.
Molecules (Basel, Switzerland)
Jul 31, 2020
In this study, a novel hybrid surrogate machine learning model based on a feedforward neural network (FNN) and one step secant algorithm (OSS) was developed to predict the load-bearing capacity of concrete-filled steel tube columns (CFST), whereas th...
Machine Learning Algorithms Identify Pathogen-Specific Biomarkers of Clinical and Metabolomic Characteristics in Septic Patients with Bacterial Infections.
BioMed research international
Jul 27, 2020
Sepsis is a high-mortality disease that is infected by bacteria, but pathogens in individual patients are difficult to diagnosis. Metabolomic changes triggered by microbial activity provide us with the possibility of accurately identifying infection....
Inexpensive, non-invasive biomarkers predict Alzheimer transition using machine learning analysis of the Alzheimer's Disease Neuroimaging (ADNI) database.
PloS one
Jul 27, 2020
The Alzheimer's Disease Neuroimaging (ADNI) database is an expansive undertaking by government, academia, and industry to pool resources and data on subjects at various stage of symptomatic severity due to Alzheimer's disease. As expected, magnetic r...
Supervised machine learning for the early prediction of acute respiratory distress syndrome (ARDS).
Journal of critical care
Jul 24, 2020
PURPOSE: Acute respiratory distress syndrome (ARDS) is a serious respiratory condition with high mortality and associated morbidity. The objective of this study is to develop and evaluate a novel application of gradient boosted tree models trained on...
Novel application of an automated-machine learning development tool for predicting burn sepsis: proof of concept.
Scientific reports
Jul 23, 2020
Sepsis is the primary cause of burn-related mortality and morbidity. Traditional indicators of sepsis exhibit poor performance when used in this unique population due to their underlying hypermetabolic and inflammatory response following burn injury....
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