AIMC Topic: Databases, Factual

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New convolutional neural network model for screening and diagnosis of mammograms.

PloS one
Breast cancer is the most common cancer in women and poses a great threat to women's life and health. Mammography is an effective method for the diagnosis of breast cancer, but the results are largely limited by the clinical experience of radiologist...

Morphological Characterization of Functional Brain Imaging by Isosurface Analysis in Parkinson's Disease.

International journal of neural systems
Finding new biomarkers to model Parkinson's Disease (PD) is a challenge not only to help discerning between Healthy Control (HC) subjects and patients with potential PD but also as a way to measure quantitatively the loss of dopaminergic neurons main...

Identifying COVID19 from Chest CT Images: A Deep Convolutional Neural Networks Based Approach.

Journal of healthcare engineering
Coronavirus Disease (COVID19) is a fast-spreading infectious disease that is currently causing a healthcare crisis around the world. Due to the current limitations of the reverse transcription-polymerase chain reaction (RT-PCR) based tests for detect...

Long-distance disorder-disorder relation extraction with bootstrapped noisy data.

Journal of biomedical informatics
OBJECTIVE: Artificial intelligence in healthcare increasingly relies on relations in knowledge graphs for algorithm development. However, many important relations are not well covered in existing knowledge graphs. We aim to develop a novel long-dista...

TISNet-Enhanced Fully Convolutional Network with Encoder-Decoder Structure for Tongue Image Segmentation in Traditional Chinese Medicine.

Computational and mathematical methods in medicine
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
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
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
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
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...