AIMC Topic: Neural Networks, Computer

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Artificial Intelligence to Detect Papilledema from Ocular Fundus Photographs.

The New England journal of medicine
BACKGROUND: Nonophthalmologist physicians do not confidently perform direct ophthalmoscopy. The use of artificial intelligence to detect papilledema and other optic-disk abnormalities from fundus photographs has not been well studied.

Resolving challenges in deep learning-based analyses of histopathological images using explanation methods.

Scientific reports
Deep learning has recently gained popularity in digital pathology due to its high prediction quality. However, the medical domain requires explanation and insight for a better understanding beyond standard quantitative performance evaluation. Recentl...

Brain Medical Image Fusion Based on Dual-Branch CNNs in NSST Domain.

BioMed research international
Computed tomography (CT) images show structural features, while magnetic resonance imaging (MRI) images represent brain tissue anatomy but do not contain any functional information. How to effectively combine the images of the two modes has become a ...

Rapid screening of hepatitis B using Raman spectroscopy and long short-term memory neural network.

Lasers in medical science
This study presents a rapid method to screen hepatitis B patients using serum Raman spectroscopy combined with long short-term memory neural network (LSTM). The serum samples taken from 435 hepatitis B patients and 699 non-hepatitis B people were mea...

Evaluating severity of white matter lesions from computed tomography images with convolutional neural network.

Neuroradiology
PURPOSE: Severity of white matter lesion (WML) is typically evaluated on magnetic resonance images (MRI), yet the more accessible, faster, and less expensive method is computed tomography (CT). Our objective was to study whether WML can be automatica...

Deep Multi-Scale Fusion Neural Network for Multi-Class Arrhythmia Detection.

IEEE journal of biomedical and health informatics
Automated electrocardiogram (ECG) analysis for arrhythmia detection plays a critical role in early prevention and diagnosis of cardiovascular diseases. Extracting powerful features from raw ECG signals for fine-grained diseases classification is stil...

Perception-to-Image: Reconstructing Natural Images from the Brain Activity of Visual Perception.

Annals of biomedical engineering
The reappearance of human visual perception is a challenging topic in the field of brain decoding. Due to the complexity of visual stimuli and the constraints of fMRI data collection, the present decoding methods can only reconstruct the basic outlin...

Predicting protein-peptide binding sites with a deep convolutional neural network.

Journal of theoretical biology
MOTIVATION: Interactions between proteins and peptides influence biological functions. Predicting such bio-molecular interactions can lead to faster disease prevention and help in drug discovery. Experimental methods for determining protein-peptide b...

Generative Adversarial Networks are special cases of Artificial Curiosity (1990) and also closely related to Predictability Minimization (1991).

Neural networks : the official journal of the International Neural Network Society
I review unsupervised or self-supervised neural networks playing minimax games in game-theoretic settings: (i) Artificial Curiosity (AC, 1990) is based on two such networks. One network learns to generate a probability distribution over outputs, the ...

Cellular community detection for tissue phenotyping in colorectal cancer histology images.

Medical image analysis
Classification of various types of tissue in cancer histology images based on the cellular compositions is an important step towards the development of computational pathology tools for systematic digital profiling of the spatial tumor microenvironme...