AIMC Topic: Data Visualization
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Comparison of computer-generated sentiment analysis to traditional meta-analysis: an infographic.
Regional anesthesia and pain medicine
Jan 12, 2022
Benchmarking and Testing Machine Learning Approaches with BARRA:CuRDa, a for Cancer Research.
Journal of computational biology : a journal of computational molecular cell biology
Jul 14, 2021
One-dimensional convolutional neural network-based active feature extraction for fault detection and diagnosis of industrial processes and its understanding via visualization.
ISA transactions
May 7, 2021
Feature extraction from process signals enables process monitoring models to be effective in industrial processes. Deep learning presents extensive possibilities for extracting abstract features from image and visual data. However, the main inputs of...
Implicit adversarial data augmentation and robustness with Noise-based Learning.
Neural networks : the official journal of the International Neural Network Society
Apr 20, 2021
We introduce a Noise-based Learning (NoL) approach for training neural networks that are intrinsically robust to adversarial attacks. We find that the learning of random noise introduced with the input with the same loss function used during posterio...
The COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: Monitoring County-Level Vulnerability Using Visualization, Statistical Modeling, and Machine Learning.
Environmental health perspectives
Jan 5, 2021
EDeepSSP: Explainable deep neural networks for exact splice sites prediction.
Journal of bioinformatics and computational biology
Jul 22, 2020
Splice site prediction is crucial for understanding underlying gene regulation, gene function for better genome annotation. Many computational methods exist for recognizing the splice sites. Although most of the methods achieve a competent performanc...
Data reduction and data visualization for automatic diagnosis using gene expression and clinical data.
Artificial intelligence in medicine
May 28, 2020
Accurate diagnoses of specific diseases require, in general, the review of the whole medical history of a patient. Currently, even though many advances have been made for disease monitoring, domain experts are still requested to perform direct analys...
Predicting Adverse Drug-Drug Interactions with Neural Embedding of Semantic Predications.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Mar 4, 2020
The identification of drug-drug interactions (DDIs) is important for patient safety; yet, compared to other pharmacovigilance work, a limited amount of research has been conducted in this space. Recent work has successfully applied a method of derivi...
A temporal visualization of chronic obstructive pulmonary disease progression using deep learning and unstructured clinical notes.
BMC medical informatics and decision making
Dec 17, 2019
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a progressive lung disease that is classified into stages based on disease severity. We aimed to characterize the time to progression prior to death in patients with COPD and to generate a t...
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