Predicting hospital readmission is crucial for improving patient care and optimizing
healthcareresource allocation. Traditional methods often overlook the imbalanced costs …

The Internet of Things (IoT) represents a transformative paradigm shift, revolutionizinghow
devices and systems interact and communicate in the digital age. However, the …

Insider threats represent a significant risk to organizational security, arising from
individualswithin the organization who have access to sensitive information and systems …

Genomic research has seen an exponential increase in data generation, necessitating
advanced analytical approaches for efficient extraction of meaningful information …

Zero-day exploits represent one of the most severe and challenging threats in the realm
ofcybersecurity. These exploits target software vulnerabilities that are unknown to the …

This research paper explores the application of deep learning techniques in natural
language processing (NLP) for electronic health records (EHRs). Electronic health records …

Precision oncology aims to deliver personalized cancer treatment by identifying biomarkers
that can predict patient response to specific therapies. Deep learning has emerged as a …

Clinical trials are a critical component of the drug discovery and development process, yet
they are often plagued by inefficiencies and high costs. Artificial intelligence (AI) offers a …

Energy-proportional computing aims to achieve optimal energy efficiency in datacenters by
ensuring that energy consumption is directly proportional to the workload. This …

Federated Learning (FL) has emerged as a promising approach for collaborative machine
learning across decentralized entities, enabling privacy-preserving data sharing. In the …