AI Medical Compendium Journal:
Methods (San Diego, Calif.)

Showing 111 to 120 of 183 articles

A self-supervised feature-standardization-block for cross-domain lung disease classification.

Methods (San Diego, Calif.)
With the advance of deep learning technology, convolutional neural network (CNN) has been wildly used and achieved the state-of-the-art performances in the area of medical image classification. However, most existing medical image classification meth...

Automated ECG classification based on 1D deep learning network.

Methods (San Diego, Calif.)
The standard 12-lead electrocardiogram (ECG) records the heart's electrical activity from electrodes on the skin, and is widely used in screening and diagnosis of the cardiac conditions due to its low price and non-invasive characteristics. Manual ex...

iRNA-m5U: A sequence based predictor for identifying 5-methyluridine modification sites in Saccharomyces cerevisiae.

Methods (San Diego, Calif.)
The 5-methyluridine (mU)modification plays important roles in a series of biological processes. Accurate identification of mU sites will be helpful to decode its biological functions. Although experimental techniques have been proposed to detect mU, ...

Comparing performance of iterative and non-iterative algorithms on various feature schemes for arrhythmia analysis.

Methods (San Diego, Calif.)
To evaluate the performance of the classic machine learning algorithms and the effectiveness of various features, the iterative algorithms (i.e., support vector machine (SVM), and least-squares SVM (LS-SVM)) and non-iterative algorithms (i.e., random...

Diagnosis of cholangiocarcinoma from microscopic hyperspectral pathological dataset by deep convolution neural networks.

Methods (San Diego, Calif.)
This paper focuses on automatic Cholangiocarcinoma (CC) diagnosis from microscopic hyperspectral (HSI) pathological dataset with deep learning method. The first benchmark based on the microscopic hyperspectral pathological images is set up. Particula...

Hybrid manifold-deep convolutional neural network for sleep staging.

Methods (San Diego, Calif.)
Analysis of electroencephalogram (EEG) is a crucial diagnostic criterion for many sleep disorders, of which sleep staging is an important component. Manual stage classification is a labor-intensive process and usually suffered from many subjective fa...

A hierarchical three-step superpixels and deep learning framework for skin lesion classification.

Methods (San Diego, Calif.)
Skin cancer is one of the most common and dangerous cancer that exists worldwide. Malignant melanoma is one of the most dangerous skin cancer types has a high mortality rate. An estimated 196,060 melanoma cases will be diagnosed in 2020 in the USA. M...