AIMC Topic: Humans

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Automated detection of colorectal tumors based on artificial intelligence.

BMC medical informatics and decision making
BACKGROUND: This study developed a diagnostic tool to automatically detect normal, unclear and tumor images from colonoscopy videos using artificial intelligence.

CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization.

IEEE transactions on visualization and computer graphics
Deep learning's great success motivates many practitioners and students to learn about this exciting technology. However, it is often challenging for beginners to take their first step due to the complexity of understanding and applying deep learning...

Pain Treatment Evaluation in COVID-19 Patients with Hesitant Fuzzy Linguistic Multicriteria Decision-Making.

Journal of healthcare engineering
The coronavirus disease 2019 (COVID-19) has emerged as a worldwide pandemic since March 2020. Although most patients complain of moderate or severe pain, these symptoms are generally underestimated and appropriate treatment is not applied. This study...

Precision Regulation Approach: A COVID-19 Triggered Regulatory Drive in South Korea.

Frontiers in public health
COVID-19 has triggered various changes in our everyday lives and how we conceptualize the functions of governments. Some areas require stricter forms of regulation while others call for deregulation. The challenge for the regulatory authorities is to...

Machine learning model for predicting severity prognosis in patients infected with COVID-19: Study protocol from COVID-AI Brasil.

PloS one
The new coronavirus, which began to be called SARS-CoV-2, is a single-stranded RNA beta coronavirus, initially identified in Wuhan (Hubei province, China) and currently spreading across six continents causing a considerable harm to patients, with no ...

Discriminative Feature Learning for Thorax Disease Classification in Chest X-ray Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
This paper focuses on the thorax disease classification problem in chest X-ray (CXR) images. Different from the generic image classification task, a robust and stable CXR image analysis system should consider the unique characteristics of CXR images....

Oxynet: A collective intelligence that detects ventilatory thresholds in cardiopulmonary exercise tests.

European journal of sport science
The problem of the automatic determination of the first and second ventilatory thresholds (VT1 and VT2) from cardiopulmonary exercise test (CPET) still leads to controversy. The reliability of the gold standard methodology (i.e. expert visual inspect...

Lung cancer prediction by Deep Learning to identify benign lung nodules.

Lung cancer (Amsterdam, Netherlands)
INTRODUCTION: Deep Learning has been proposed as promising tool to classify malignant nodules. Our aim was to retrospectively validate our Lung Cancer Prediction Convolutional Neural Network (LCP-CNN), which was trained on US screening data, on an in...

ES-ARCNN: Predicting enhancer strength by using data augmentation and residual convolutional neural network.

Analytical biochemistry
Enhancers are non-coding DNA sequences bound by proteins called transcription factors. They function as distant regulators of gene transcription and participate in the development and maintenance of cell types and tissues. Since experimental validati...