AIMC Topic: Deep Learning

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Early Alzheimer's disease diagnosis based on EEG spectral images using deep learning.

Neural networks : the official journal of the International Neural Network Society
Early diagnosis of Alzheimer's disease (AD) is a proceeding hot issue along with a sharp upward trend in the incidence rate. Recently, early diagnosis of AD employing Electroencephalogram (EEG) as a specific hallmark has been an increasingly signific...

Dual-energy CT for automatic organs-at-risk segmentation in brain-tumor patients using a multi-atlas and deep-learning approach.

Scientific reports
In radiotherapy, computed tomography (CT) datasets are mostly used for radiation treatment planning to achieve a high-conformal tumor coverage while optimally sparing healthy tissue surrounding the tumor, referred to as organs-at-risk (OARs). Based o...

NetSurfP-2.0: Improved prediction of protein structural features by integrated deep learning.

Proteins
The ability to predict local structural features of a protein from the primary sequence is of paramount importance for unraveling its function in absence of experimental structural information. Two main factors affect the utility of potential predict...

Detection of broadleaf weeds growing in turfgrass with convolutional neural networks.

Pest management science
BACKGROUND: Weed infestations reduce turfgrass aesthetics and uniformity. Postemergence (POST) herbicides are applied uniformly on turfgrass, hence areas without weeds are also sprayed. Deep learning, particularly the architecture of convolutional ne...

Deep learning-based super-resolution in coherent imaging systems.

Scientific reports
We present a deep learning framework based on a generative adversarial network (GAN) to perform super-resolution in coherent imaging systems. We demonstrate that this framework can enhance the resolution of both pixel size-limited and diffraction-lim...

Unsupervised classification of multi-omics data during cardiac remodeling using deep learning.

Methods (San Diego, Calif.)
Integration of multi-omics in cardiovascular diseases (CVDs) presents high potentials for translational discoveries. By analyzing abundance levels of heterogeneous molecules over time, we may uncover biological interactions and networks that were pre...

Multi-organ segmentation of the head and neck area: an efficient hierarchical neural networks approach.

International journal of computer assisted radiology and surgery
PURPOSE: In radiation therapy, a key step for a successful cancer treatment is image-based treatment planning. One objective of the planning phase is the fast and accurate segmentation of organs at risk and target structures from medical images. Howe...

Effects of Food Contamination on Gastrointestinal Morbidity: Comparison of Different Machine-Learning Methods.

International journal of environmental research and public health
Morbidity prediction can be useful in improving the effectiveness and efficiency of medical services, but accurate morbidity prediction is often difficult because of the complex relationships between diseases and their influencing factors. This study...

A deep learning approach to automatic teeth detection and numbering based on object detection in dental periapical films.

Scientific reports
We propose using faster regions with convolutional neural network features (faster R-CNN) in the TensorFlow tool package to detect and number teeth in dental periapical films. To improve detection precisions, we propose three post-processing techniqu...