AIMC Topic: Neural Networks, Computer

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Development of an artificial intelligence-based algorithm for the detection of left atrial enlargement from feline thoracic radiographs.

The veterinary quarterly
A heart-convolutional neural network (heart-CNN) was developed and tested for the automatic detection of left atrial enlargement (LAE) from feline thoracic radiographs. A retrospective and multicenter study was performed. Right lateral and dorso-vent...

Semi-Supervised Fatty Liver Classification Using Attention-Based Graph Neural Network Models.

Journal of Korean medical science
BACKGROUND: Fatty liver disease is a common condition linked to metabolic syndrome, cardiovascular diseases, and liver cirrhosis, and timely, accurate diagnosis is crucial. In clinical studies, incorporating deep learning models often faces the chall...

Modeling regional mean sea level based on climate measurements using a stacked ensemble approach.

Environmental monitoring and assessment
Assessing changes in mean sea level (MSL) has become increasingly critical due to the significance of climate changes. Soft computing techniques are now widely used to reduce the time and cost associated with traditional MSL estimation methods. Histo...

A novel hybrid model for emotion detection in text through sequential and transformer-based approaches: LSTM enhanced RoBERTa (LER).

Scientific reports
Text emotion detection is an essential task in Natural Language Processing (NLP), with applications in customer support automation, diagnosing mental health, and social media analysis. Yet, precise emotion detection is a difficult problem as human em...

Predicting human decision-making across task conditions via individuality transfer.

eLife
Predicting an individual's behavior in one task condition based on their behavior in a different condition is a key challenge in modeling individual decision-making tendencies. We propose a novel framework that addresses this challenge by leveraging ...

Artificial intelligence-enabled "inherited noninvasive intracellular recording" for prolonged monitoring of cardiac action potentials.

Science advances
Intracellular action potential (AP) recording that allows long-term monitoring is challenging because permanent membrane penetration is impossible due to cell death or resealing of perforated cell membrane. Herein, an "inherited noninvasive intracell...

Biologically informed cortical models predict optogenetic perturbations.

eLife
A recurrent neural network fitted to large electrophysiological datasets may help us understand the chain of cortical information transmission. In particular, successful network reconstruction methods should enable a model to predict the response to ...

A legal judgment prediction model based on knowledge fusion and dependency masking.

PloS one
Legal Judgment Prediction (LJP) is a core task in Legal AI systems, which aims to predict law articles, charges, and term-of-penalty from case facts. While existing deep-learning-based LJP approaches for civil law systems have achieved certain progre...

A hybrid CNN-ViT based framework for automatic traffic actions detection in smart cities.

PloS one
It is crucial to automatically detect traffic accidents and hazardous situations in a timely and accurate manner. In this way, both individual security will be ensured and significant contributions will be made to economic efficiency and sustainable ...

Deep learning with satellite images enables high-resolution income estimation: A case study of Buenos Aires.

PloS one
High-resolution income data is crucial for informing policy decisions as it allows policymakers to better understand the distribution of wealth and poverty. However, obtaining this information is often cost-prohibitive, especially in developing count...