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DeepASDPred: a CNN-LSTM-based deep learning method for Autism spectrum disorders risk RNA identification.

BMC bioinformatics
BACKGROUND: Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders characterized by difficulty communicating with society and others, behavioral difficulties, and a brain that processes information differently than normal. Geneti...

Developing a User-Friendly Code for the Fast Estimation of Well-Behaved Real-Space Partial Charges.

Journal of chemical information and modeling
The Quantum Theory of Atoms in Molecules (QTAIM) provides an intuitive, yet physically sound, strategy to determine the partial charges of any chemical system relying on the topology induced by the electron density ρ() . In a previous work [ , , 0141...

Performance of active learning models for screening prioritization in systematic reviews: a simulation study into the Average Time to Discover relevant records.

Systematic reviews
BACKGROUND: Conducting a systematic review demands a significant amount of effort in screening titles and abstracts. To accelerate this process, various tools that utilize active learning have been proposed. These tools allow the reviewer to interact...

Highly automatic and universal approach for pure ion chromatogram construction from liquid chromatography-mass spectrometry data using deep learning.

Journal of chromatography. A
Feature extraction is the most fundamental step when analyzing liquid chromatography-mass spectrometry (LC-MS) datasets. However, traditional methods require optimal parameter selections and re-optimization for different datasets, thus hindering effi...

SnapEnsemFS: a snapshot ensembling-based deep feature selection model for colorectal cancer histological analysis.

Scientific reports
Colorectal cancer is the third most common type of cancer diagnosed annually, and the second leading cause of death due to cancer. Early diagnosis of this ailment is vital for preventing the tumours to spread and plan treatment to possibly eradicate ...

Automatic Extraction of Comprehensive Drug Safety Information from Adverse Drug Event Narratives in the Korea Adverse Event Reporting System Using Natural Language Processing Techniques.

Drug safety
INTRODUCTION: Concerns have been raised over the quality of drug safety information, particularly data completeness, collected through spontaneous reporting systems (SRS), although regulatory agencies routinely use SRS data to guide their pharmacovig...

Evolving a Pipeline Approach for Abstract Meaning Representation Parsing Towards Dynamic Neural Networks.

International journal of neural systems
Meaning Representation parsing aims to represent a sentence as a structured, Directed, Acyclic Graph (DAG), in an attempt to extract meaning from text. This paper extends an existing 2-stage pipeline AMR parser with state-of-the-art techniques in dep...

Consistency of Artificial Intelligence (AI)-based Diagnostic Support Software in Short-term Digital Mammography Reimaging After Core Needle Biopsy.

Journal of digital imaging
To evaluate the consistency in the performance of Artificial Intelligence (AI)-based diagnostic support software in short-term digital mammography reimaging after core needle biopsy. Of 276 women who underwent short-term (<3 mo) serial digital mammog...

FrMLNet: Framelet-Based Multilevel Network for Pansharpening.

IEEE transactions on cybernetics
Most modern satellites can provide two types of images: 1) panchromatic (PAN) image and 2) multispectral (MS) image. The former has high spatial resolution and low spectral resolution, while the latter has high spectral resolution and low spatial res...

mEMbrain: an interactive deep learning MATLAB tool for connectomic segmentation on commodity desktops.

Frontiers in neural circuits
Connectomics is fundamental in propelling our understanding of the nervous system's organization, unearthing cells and wiring diagrams reconstructed from volume electron microscopy (EM) datasets. Such reconstructions, on the one hand, have benefited ...