AIMC Topic: Deep Learning

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Hybrid model integration with explainable AI for brain tumor diagnosis: a unified approach to MRI analysis and prediction.

Scientific reports
Effective treatment for brain tumors relies on accurate detection because this is a crucial health condition. Medical imaging plays a pivotal role in improving tumor detection and diagnosis in the early stage. This study presents two approaches to th...

Deep learning for occupation recognition and knowledge discovery in rheumatology clinical notes.

Scientific reports
Occupational data is a crucial social determinant of health, influencing diagnostic accuracy, treatment strategies, and policy-making in healthcare. However, its inclusion in electronic health records (EHR) is often relegated to unstructured fields. ...

Gesture recognition for hearing impaired people using an ensemble of deep learning models with improving beluga whale optimization-based hyperparameter tuning.

Scientific reports
Sign language (SL) is the linguistics of speech and hearing-impaired individuals. The hand gesture is the primary model employed in SL by speech and hearing-challenged people to talk with themselves and ordinary persons. At present, hand gesture dete...

Predict the degree of secondary structures of the encoding sequences in DNA storage by deep learning model.

Scientific reports
DNA storage has been widely considered as a promising alternative for exponentially growing data. However, the inherent complex secondary structures severely compromise the processes of synthesis, PCR amplification, and sequencing, interfering with r...

A hybrid compound scaling hypergraph neural network for robust cervical cancer subtype classification using whole slide cytology images.

Scientific reports
Cervical cancer is a major cause of mortality among women, particularly in low-income countries with insufficient screening programs. Manual cytological examination is time-consuming, error-prone and subject to inter-observer variability. Automated a...

A fake news detection model using the integration of multimodal attention mechanism and residual convolutional network.

Scientific reports
To improve the accuracy and efficiency of fake news detection, this study proposes a deep learning model that integrates residual networks with attention mechanisms. Building on traditional convolutional neural networks, the model incorporates multi-...

Innovative deep learning classifiers for breast cancer detection through hybrid feature extraction techniques.

Scientific reports
Breast cancer remains a major cause of mortality among women, where early and accurate detection is critical to improving survival rates. This study presents a hybrid classification approach for mammogram analysis by combining handcrafted statistical...

Blockchain enabled deep learning model with modified coati optimization for sustainable healthcare disease detection and classification.

Scientific reports
The growing number of patients and the emergence of new symptoms and diseases make health monitoring and assessment increasingly complex for medical staff and hospitals. The execution of big and heterogeneous data gathered by medical sensors and the ...

Multiclass semantic segmentation for prime disease detection with severity level identification in Citrus plant leaves.

Scientific reports
Agriculture provides the basics for producing food, driving economic growth, and maintaining environmental sustainability. On the other hand, plant diseases have the potential to reduce crop productivity and raise expenses, posing a risk to food secu...

BGATT-GR: accurate identification of glucocorticoid receptor antagonists based on data augmentation combined with BiGRU-attention.

Scientific reports
The glucocorticoid receptor (GR) is a critical nuclear receptor that regulates a broad spectrum of physiological functions, including stress adaptation, immune response, and metabolism. Given the association between aberrant GR signaling and various ...