The Internet of Things (IoT) will disrupt medicine the most. Healthcare uses edge computing,
deep learning, IoT, and machine learning for real-time analytics, monitoring, and data …

Data anomalies are found using anomaly detection. Generative adversarial networks
(GANs) can produce synthetic data and learn complex patterns. Temporal dependencies …

This research aimed to evaluate numerous deep-learning models for Alzheimer's disease
detection using several different neuroimaging techniques. Ten recent studies were selected …

This research used a wearable sensor to gather photoplethysmography (PPG) signals from
15 healthy subjects. The dataset includes 7,308 PPG segments, each containing 8 seconds …

The most frequent primary brain tumors are gliomas, which call for precise prognostic
models for early detection and individualized care. For optimum treatment planning and …

Critical data and systems are now more frequently kept and analyzed in the cloud as a result
of the cloud computing industry's quick development. As enterprises trust valuable …

This study primarily examines how well four pretrained deep learning models perform in
identifying eye disorders using four metrics we developed: recall, precision, accuracy, and …

Parkinson's disease is a degenerative condition that greatly affects the population,
especially the elderly. The main cause is the gradual death of melanocytes in the brain …

The creation of renewable energy relies heavily on wind turbines, yet undiscovered defects
can reduce its performance. This study uses an ensemble methodology to propose a …

The Web of Things is an organization of interconnected gadgets and sensors intended to
speak with one another and trade data flawlessly. The enormous measure of information …