Vol. 2 No. 4 (2024): Volume-II, Number-IV, 2024
-
Quantum Neural Networks for Accelerating Drug Discovery in Regenerative Medicine
Abstract 10
Regenerative medicine requires rapid analysis of the best therapeutic molecules capable of interacting with in vivo undifferentiated mass with complex biology and therapeutic properties that are needed to repair and regenerate tissues. The scalability and efficiency of conventional computational solutions and even recent representations with more advanced classical neural networks are limited w ... read more
-
AI-Driven Anomaly Detection for Financial Fraud A Hybrid Approach Using Graph Neural Networks and Time-Series Analysis
Abstract 11
Financial fraud is a serious risk affecting the stability of world markets since loss to financial fraud laid billions of dollars every year, studies challenge the conventional methods of detection. The complex pattern of relations and temporal trends in the fraudulent operations cannot be easily observed by conventional rule-based and statistical methods. [1][2] The paper why constructs a hybr ... read more
-
Deep Learning vs. Financial Fraud Real-Time Detection in High-Frequency Trading
Abstract 11
HFT systems are sensitive to microseconds, and generate order-book streams that present novel challenges to the detection of fraud-related behaviors like spoofing and layering. Current algebraic-based surveillance strategies are ineffective in describing the nonlinear temporal patterns and subtle manipulation schemes that exist in contemporary financial markets since these strategies are typica ... read more
-
Machine Learning-Based Clinical Decision Support Systems for Personalized Stem Cell Treatments in Regenerative Medicine
Abstract 10
The incorporation of machine learning (ML) into clinical decision support systems (CDSS) has brought new possibilities for the further development of personalized stem cell therapies in the field of regenerative medicine. Furthermore, ML-based CDSS ae) provide a characterization of disease and patient-specific information (e.g., genomic profiles, biomarker levels, clinical histories), b) assist ... read more