AI Medical Compendium Topic:
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Deep learning based sentiment analysis and offensive language identification on multilingual code-mixed data.

Scientific reports
Sentiment analysis is a process in Natural Language Processing that involves detecting and classifying emotions in texts. The emotion is focused on a specific thing, an object, an incident, or an individual. Although some tasks are concerned with det...

Automatic Gender and Age Classification from Offline Handwriting with Bilinear ResNet.

Sensors (Basel, Switzerland)
This work focuses on automatic gender and age prediction tasks from handwritten documents. This problem is of interest in a variety of fields, such as historical document analysis and forensic investigations. The challenge for automatic gender and ag...

TripletProt: Deep Representation Learning of Proteins Based On Siamese Networks.

IEEE/ACM transactions on computational biology and bioinformatics
Pretrained representations have recently gained attention in various machine learning applications. Nonetheless, the high computational costs associated with training these models have motivated alternative approaches for representation learning. Her...

Machine understanding surgical actions from intervention procedure textbooks.

Computers in biology and medicine
The automatic extraction of procedural surgical knowledge from surgery manuals, academic papers or other high-quality textual resources, is of the utmost importance to develop knowledge-based clinical decision support systems, to automatically execut...

From Show to Tell: A Survey on Deep Learning-Based Image Captioning.

IEEE transactions on pattern analysis and machine intelligence
Connecting Vision and Language plays an essential role in Generative Intelligence. For this reason, large research efforts have been devoted to image captioning, i.e. describing images with syntactically and semantically meaningful sentences. Startin...

Deep Learning in the Detection of Disinformation about COVID-19 in Online Space.

Sensors (Basel, Switzerland)
This article focuses on the problem of detecting disinformation about COVID-19 in online discussions. As the Internet expands, so does the amount of content on it. In addition to content based on facts, a large amount of content is being manipulated,...

SGORNN: Combining scalar gates and orthogonal constraints in recurrent networks.

Neural networks : the official journal of the International Neural Network Society
Recurrent Neural Network (RNN) models have been applied in different domains, producing high accuracies on time-dependent data. However, RNNs have long suffered from exploding gradients during training, mainly due to their recurrent process. In this ...

No need to forget, just keep the balance: Hebbian neural networks for statistical learning.

Cognition
Language processing in humans has long been proposed to rely on sophisticated learning abilities including statistical learning. Endress and Johnson (E&J, 2021) recently presented a neural network model for statistical learning based on Hebbian learn...

Human-level play in the game of by combining language models with strategic reasoning.

Science (New York, N.Y.)
Despite much progress in training artificial intelligence (AI) systems to imitate human language, building agents that use language to communicate intentionally with humans in interactive environments remains a major challenge. We introduce Cicero, t...

An imConvNet-based deep learning model for Chinese medical named entity recognition.

BMC medical informatics and decision making
BACKGROUND: With the development of current medical technology, information management becomes perfect in the medical field. Medical big data analysis is based on a large amount of medical and health data stored in the electronic medical system, such...