AI Medical Compendium Topic

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Transforming the study of organisms: Phenomic data models and knowledge bases.

PLoS computational biology
The rapidly decreasing cost of gene sequencing has resulted in a deluge of genomic data from across the tree of life; however, outside a few model organism databases, genomic data are limited in their scientific impact because they are not accompanie...

pcPromoter-CNN: A CNN-Based Prediction and Classification of Promoters.

Genes
A promoter is a small region within the DNA structure that has an important role in initiating transcription of a specific gene in the genome. Different types of promoters are recognized by their different functions. Due to the importance of promoter...

Fine-Tuning Word Embeddings for Hierarchical Representation of Data Using a Corpus and a Knowledge Base for Various Machine Learning Applications.

Computational and mathematical methods in medicine
Word embedding models have recently shown some capability to encode hierarchical information that exists in textual data. However, such models do not explicitly encode the hierarchical structure that exists among words. In this work, we propose a met...

Feature Selection on Elite Hybrid Binary Cuckoo Search in Binary Label Classification.

Computational and mathematical methods in medicine
For the low optimization accuracy of the cuckoo search algorithm, a new search algorithm, the Elite Hybrid Binary Cuckoo Search (EHBCS) algorithm, is improved by feature weighting and elite strategy. The EHBCS algorithm has been designed for feature ...

Classification aware neural topic model for COVID-19 disinformation categorisation.

PloS one
The explosion of disinformation accompanying the COVID-19 pandemic has overloaded fact-checkers and media worldwide, and brought a new major challenge to government responses worldwide. Not only is disinformation creating confusion about medical scie...

Cross Knowledge-based Generative Zero-Shot Learning approach with Taxonomy Regularization.

Neural networks : the official journal of the International Neural Network Society
Although zero-shot learning (ZSL) has an inferential capability of recognizing new classes that have never been seen before, it always faces two fundamental challenges of the cross modality and cross-domain challenges. In order to alleviate these pro...

Fast convergence rates of deep neural networks for classification.

Neural networks : the official journal of the International Neural Network Society
We derive the fast convergence rates of a deep neural network (DNN) classifier with the rectified linear unit (ReLU) activation function learned using the hinge loss. We consider three cases for a true model: (1) a smooth decision boundary, (2) smoot...

Long-term Cognitive Network-based architecture for multi-label classification.

Neural networks : the official journal of the International Neural Network Society
This paper presents a neural system to deal with multi-label classification problems that might involve sparse features. The architecture of this model involves three sequential blocks with well-defined functions. The first block consists of a multil...

Block-cyclic stochastic coordinate descent for deep neural networks.

Neural networks : the official journal of the International Neural Network Society
We present a stochastic first-order optimization algorithm, named block-cyclic stochastic coordinate descent (BCSC), that adds a cyclic constraint to stochastic block-coordinate descent in the selection of both data and parameters. It uses different ...

Identification of diatom taxonomy by a combination of region-based full convolutional network, online hard example mining, and shape priors of diatoms.

International journal of legal medicine
Diatom test is one of the commonly used diagnostic methods for drowning in forensic pathology, which provides supportive evidence for drowning. However, in forensic practice, it is time-consuming and laborious for forensic experts to classify and cou...