Vol. 3 No. 1 (2025): Volume-III, Number-I, 2025
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Blockchain, AI and Quantum Networks: A Tri-Layer Modelfor Secure Transactions in Finance and Healthcare
Abstract 30
Rapid digitization of financial and healthcare services has produced immense value while also increasing systemic vulnerability: sensitive transactions and records must be exchanged across complex, heterogeneous ecosystems subject to cyber-attacks, fraud, and regulatory scrutiny. In parallel, three technological trends distributed ledger technologies (blockchain), artificial intelligence (A ... read more
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Bridging Actuarial Science and Quantum Machine Learning: Applications in Health Insurance
Abstract 34
This paper presents a comprehensive framework for integrating Quantum Machine situating the problem: rising healthcare costs and the increasing complexity of health-claims data demand more powerful predictive models than standard generalized linear models (GLMs) alone can reliably deliver. We review classical actuarial techniques and contemporary Learning (QML) into actuarial prediction pipelin ... read more
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Leveraging Quantum Machine Learning for Actuarial Predictions in Health Insurance
Abstract 35
Health insurance actuarial science has traditionally relied on classical statistical models to predict claims, assess risk, and set premiums. However, the growing complexity and high dimensionality of healthcare datasets challenge conventional techniques. Quantum Machine Learning (QML), integrating quantum computing and artificial intelligence, presents a promising paradigm for accelerating com ... read more
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Personalized Health Interventions Using AI and Wearable Data: A Data Science Pipeline Approach
Abstract 18
The integration of artificial intelligence (AI), wearable devices, and data science has inaugurated a transformative era in healthcare delivery. Wearables are increasingly ubiquitous, offering real-time, multimodal physiological data that extend beyond traditional clinical settings. Yet, despite their potential, translating raw wearable data into meaningful, personalized health interventions re ... read more
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Trustworthy Multi-Modal AI in Healthcare: A Comprehensive Framework for Bias Detection, Explanation, and Mitigation
Abstract 12
Machine learning (ML) and multi-modal artificial intelligence (AI) promise transformative improvements in healthcare: earlier diagnosis, personalized treatment, and system-level efficiency. Yet these promises are coupled with well-documented risks algorithmic bias, opacity, and fragile generalization that can exacerbate health inequities and undermine trust. This paper proposes a principled, re ... read more