Real-Time Healthcare Workforce Rescheduling using a Quantum Computer: A Novel Approach to Dynamic Staff Allocation in Hospital Settings (Published)
Real-time healthcare workforce scheduling represents a critical optimization challenge with direct implications for patient care quality and operational efficiency. This article introduces a quantum computing approach to dynamic hospital staff rescheduling that addresses the complex constraints of medical workforce allocation when facing unexpected absences. By formulating the problem as a quadratic unconstrained binary optimization (QUBO) model suitable for quantum processing, demonstrate how quantum annealing and gate-based quantum algorithms can rapidly identify optimal staff substitutions while balancing factors such as specialist qualifications, shift duration, fatigue management, and geographical proximity. The simulation results indicate that quantum-accelerated scheduling can significantly reduce the average time to fill critical absences compared to classical heuristic methods while maintaining high adherence to staffing quality metrics. This has substantial potential to mitigate the downstream clinical impacts of staffing disruptions, particularly in high-acuity hospital departments where timely specialist presence is essential for patient outcomes.
Keywords: QUBO optimization, healthcare operations, healthcare workforce management, quantum computing, staff scheduling
Quantum Computing: Revolutionizing Cloud-Based Financial Transaction Processing (Published)
Quantum computing integration into cloud-based financial transaction processing significantly enhances the financial technology sector’s capabilities. This convergence merges quantum principles with financial operations to improve data processing, security protocols, and risk management. Quantum-enabled systems deliver faster processing speeds while implementing Quantum Key Distribution for advanced cryptographic security and developing more accurate fraud detection algorithms. Financial institutions utilizing these technologies have documented measurable improvements in operational efficiency, with transaction processing times reduced by up to 85% compared to classical computing systems. Additionally, quantum-optimized trading algorithms demonstrate 23% higher returns with 17% lower volatility across tested market conditions. The quantum advantage extends to portfolio management, where optimization routines process complex risk-return scenarios 40 times faster than conventional methods. Customer response metrics indicate 91% satisfaction with the enhanced security features and reduced processing latencies. Market analysis reveals that early adopters gain substantial competitive advantages through improved risk assessment accuracy and operational cost reductions of approximately 32%. The integration establishes new performance and security benchmarks in financial services, positioning quantum computing as an increasingly essential component of financial infrastructure as the technology matures and becomes more accessible.
Keywords: Risk Management, cloud infrastructure, financial technology, quantum computing, quantum cryptography, transaction processing
Testing Healthcare AI Algorithms with Quantum Computing: Enhancing Validation and Accuracy (Published)
Due to its capacity to handle information in fundamentally new ways, leading to computational powers that were previously unreachable, the multidisciplinary subject of quantum computing has recently grown and attracted significant interest from both academia and industry. Quantum computing has great promise, but how exactly it will change healthcare is still largely unknown. The potential of quantum computing to transform compute-intensive healthcare tasks like drug discovery, personalized medicine, DNA sequencing, medical imaging, and operational optimization is the primary focus of this survey paper, which offers the first comprehensive analysis of quantum computing’s diverse capabilities in improving healthcare systems. A new era in healthcare is on the horizon, thanks to quantum computing and AI coming together to transform complicated biological simulations, the processing of genetic data, and advances in drug development. Biological data may be extremely large and complicated, making it difficult for traditional computing tools to handle. This slows down and impairs the accuracy of medical discoveries. Combining the predictive power of AI with the exponential processing speed of quantum computers presents a game-changing opportunity to speed up biological research and clinical applications. The function of quantum machine learning in improving drug discovery molecular dynamics simulations powered by artificial intelligence is discussed in this article. Quickly modeling chemical interactions, analyzing drug-receptor binding affinities, and predicting pharmacokinetics with extraordinary precision are all possible with quantum-enhanced algorithms. To further improve disease progression prediction and therapeutic target identification, we also investigate quantum-assisted deep learning models for understanding complex biological processes like protein folding, epigenetic changes, and connections between metabolic pathways.
Keywords: AI, CNN, Healthcare, quantum computing, reinforcement learning