AIMC Topic: Neural Networks, Computer

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Enhanced Regularized Ensemble Encoderdecoder Network for Accurate Brain Tumor Segmentation.

Current medical imaging
BACKGROUND: Segmenting tumors in MRI scans is a difficult and time-consuming task for radiologists. This is because tumors come in different shapes, sizes, and textures, making them hard to identify visually.

Deep Learning-based Glaucoma Detection Using CNN and Digital Fundus Images: A Promising Approach for Precise Diagnosis.

Current medical imaging
BACKGROUND: Glaucoma is a significant cause of irreversible blindness worldwide, with symptoms often going undetected until the patient's visual field starts shrinking.

Coronary heart disease classification using deep learning approach with feature selection for improved accuracy.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Coronary heart disease (CHD) is one of the deadliest diseases and a risk prediction model for cardiovascular conditions is needed. Due to the huge number of features that lead to heart problems, it is often difficult for an expert to eval...

LSTM-SAGDTA: Predicting Drug-target Binding Affinity with an Attention Graph Neural Network and LSTM Approach.

Current pharmaceutical design
INTRODUCTION: Drug development is a challenging and costly process, yet it plays a crucial role in improving healthcare outcomes. Drug development requires extensive research and testing to meet the demands for economic efficiency, cures, and pain re...

Data-driven modelling of brain activity using neural networks, diffusion maps, and the Koopman operator.

Chaos (Woodbury, N.Y.)
We propose a machine-learning approach to construct reduced-order models (ROMs) to predict the long-term out-of-sample dynamics of brain activity (and in general, high-dimensional time series), focusing mainly on task-dependent high-dimensional fMRI ...

Coronary heart disease prediction based on hybrid deep learning.

The Review of scientific instruments
Machine learning provides increasingly reliable assistance for medical experts in diagnosing coronary heart disease. This study proposes a deep learning hybrid model based coronary heart disease (CAD) prediction method, which can significantly improv...

Multimodal feature fusion in deep learning for comprehensive dental condition classification.

Journal of X-ray science and technology
BACKGROUND: Dental health issues are on the rise, necessitating prompt and precise diagnosis. Automated dental condition classification can support this need.

A Review on the Recent Advancements and Artificial Intelligence in Tablet Technology.

Current drug targets
BACKGROUND: Tablet formulation could be revolutionized by the integration of modern technology and established pharmaceutical sciences. The pharmaceutical sector can develop tablet formulations that are not only more efficient and stable but also pat...

Present and Future Innovations in AI and Cardiac MRI.

Radiology
Cardiac MRI is used to diagnose and treat patients with a multitude of cardiovascular diseases. Despite the growth of clinical cardiac MRI, complicated image prescriptions and long acquisition protocols limit the specialty and restrain its impact on ...

Research on breast cancer pathological image classification method based on wavelet transform and YOLOv8.

Journal of X-ray science and technology
 Breast cancer is one of the cancers with high morbidity and mortality in the world, which is a serious threat to the health of women. With the development of deep learning, the recognition about computer-aided diagnosis technology is getting higher ...