Computer science and information technology
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Ethical Considerations in the Design and Implementation of Healthcare Technologies
— The rapid advancement of healthcare technologies, including artificial intelligence (AI), telemedicine, electronic health records (EHRs), wearable devices, and biotechnology, has revolutionized patient care, diagnosis, and treatment. However, these innovations also raise significant ethical concerns, such…
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Customer Retention Strategies: Machine Learning’s Impact on Real-Time Analytics
— Customer retention has become increasingly dependent on organizations’ capacity to detect behavioral change before disengagement develops into actual customer churn. Recent machine learning research has substantially improved churn prediction, yet many implementations remain based on…
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Machine Learning Interpretability and Pharmacist Trust
— As machine learning (ML) systems begin to inform dispensing checks, antimicrobial stewardship, medication therapy management, and pharmacovigilance, the question is no longer whether pharmacists will encounter algorithmic recommendations, but whether—and under what conditions—they will trust…
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Cloud-Based Data Platforms for Pharmacy Research Collaboration
— Pharmacy research increasingly depends on accessing, combining, and analyzing large, heterogeneous datasets—ranging from electronic health records and dispensing logs to pharmacovigilance reports, wearables, and social determinants of health. Traditional, siloed infrastructures struggle to support this…
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Blockchain Interoperability for Sharing Immunization Records
— Immunization records underpin disease surveillance, continuity of care, and rapid verification during school admissions, employment screenings, and cross-border travel. Yet these records are fragmented across electronic health record (EHR) vendors, national/state registries, and paper cards,…
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Evaluating AI-Based Prescription Error Detection Systems in Hospital Pharmacies
— Medication safety remains a critical quality and patient-safety priority in hospital pharmacies. Traditional approaches—prospective order review, pharmacist verification, and computerized provider order entry (CPOE) with static rules—reduce error rates but struggle with context, scale, and…
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Machine Learning Models for Personalized Medication Adherence Interventions in Chronic Disease Management
Medication nonadherence is a persistent barrier to effective chronic disease management, leading to preventable morbidity, hospitalizations, and costs. Traditional, one-size-fits-all adherence programs (e.g., reminder calls, generic SMS messages) rarely account for the heterogeneous and dynamic drivers…
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SAP–MES Integration Patterns for Real-Time Production Cost Booking and Variance Analysis
In modern manufacturing environments, the ability to synchronize shop-floor operations with enterprise-level financial systems is essential for achieving real-time cost transparency and operational excellence. This paper examines integration patterns between SAP ERP/SAP S/4HANA and Manufacturing Execution…
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AI-Augmented Document Review for Regulatory Affairs Efficiency
The escalating complexity and volume of regulatory submissions in the life sciences and pharmaceutical industries have created significant burdens for regulatory affairs (RA) teams tasked with ensuring dossier accuracy, completeness, and timeliness. Traditional manual review workflows—characterized…
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Automation in Regulatory Document Compilation for ANDA Submissions
— The submission of an Abbreviated New Drug Application (ANDA) to regulatory agencies such as the U.S. Food and Drug Administration (FDA) necessitates the assembly of extensive technical, scientific, and administrative documentation. Traditionally, this process has…