AIMC Topic: Algorithms

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DeepMF: deciphering the latent patterns in omics profiles with a deep learning method.

BMC bioinformatics
BACKGROUND: With recent advances in high-throughput technologies, matrix factorization techniques are increasingly being utilized for mapping quantitative omics profiling matrix data into low-dimensional embedding space, in the hope of uncovering ins...

Image reconstruction for sub-sampled atomic force microscopy images using deep neural networks.

Micron (Oxford, England : 1993)
Undersampling is a simple but efficient way to increase the imaging rate of atomic force microscopy (AFM). One major challenge in this approach is that of accurate image reconstruction from a limited number of measurements. In this work, we present a...

DMCNN: A Deep Multiscale Convolutional Neural Network Model for Medical Image Segmentation.

Journal of healthcare engineering
Medical image segmentation is one of the hot issues in the related area of image processing. Precise segmentation for medical images is a vital guarantee for follow-up treatment. At present, however, low gray contrast and blurred tissue boundaries ar...

A novel model for malaria prediction based on ensemble algorithms.

PloS one
BACKGROUND AND OBJECTIVE: Most previous studies adopted single traditional time series models to predict incidences of malaria. A single model cannot effectively capture all the properties of the data structure. However, a stacking architecture can s...

Mitochondria Segmentation From EM Images via Hierarchical Structured Contextual Forest.

IEEE journal of biomedical and health informatics
Delineation of mitochondria from electron microscopy (EM) images is crucial to investigate its morphology and distribution, which are directly linked to neural dysfunction. However, it is a challenging task due to the varied appearances, sizes and sh...

Natural language processing for automated detection of incidental durotomy.

The spine journal : official journal of the North American Spine Society
BACKGROUND: Incidental durotomy is a common intraoperative complication during spine surgery with potential implications for postoperative recovery, patient-reported outcomes, length of stay, and costs. To our knowledge, there are no processes availa...

High-Throughput Prediction of MHC Class I and II Neoantigens with MHCnuggets.

Cancer immunology research
Computational prediction of binding between neoantigen peptides and major histocompatibility complex (MHC) proteins can be used to predict patient response to cancer immunotherapy. Current neoantigen predictors focus on estimation of MHC binding aff...

Performance of a deep learning algorithm for the evaluation of CAD-RADS classification with CCTA.

Atherosclerosis
BACKGROUND AND AIMS: Artificial intelligence (AI) is increasing its role in diagnosis of patients with suspicious coronary artery disease. The aim of this manuscript is to develop a deep convolutional neural network (CNN) to classify coronary compute...

Junctionless Poly-GeSn Ferroelectric Thin-Film Transistors with Improved Reliability by Interface Engineering for Neuromorphic Computing.

ACS applied materials & interfaces
Ferroelectric HfZrO (Fe-HZO) with a larger remnant polarization () is achieved by using a poly-GeSn film as a channel material as compared with a poly-Ge film because of the lower thermal expansion that induces higher stress. Then two-stage interface...

Accurate and rapid background estimation in single-molecule localization microscopy using the deep neural network BGnet.

Proceedings of the National Academy of Sciences of the United States of America
Background fluorescence, especially when it exhibits undesired spatial features, is a primary factor for reduced image quality in optical microscopy. Structured background is particularly detrimental when analyzing single-molecule images for 3-dimens...