Computer science and information technology
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Development of Smart Drug Delivery Systems Using Internet of Things (IoT) Technology
The integration of Internet of Things (IoT) technology into healthcare has heralded a transformative era in medical treatment and patient management. Smart drug delivery systems, as an emerging subset of this transformation, aim to enhance the…
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ECommerce Innovation Through Cloud Platforms
E-commerce has evolved dramatically in recent years, driven by advancements in technology, particularly cloud computing. The integration of cloud platforms into e-commerce ecosystems has revolutionized the way businesses operate, offering scalability, flexibility, and enhanced customer experiences.…
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Development of AI-Based Drug Formulations for Personalized Medicine
Personalized medicine represents a paradigm shift in healthcare by tailoring treatment strategies to individual patient characteristics. In recent years, artificial intelligence (AI) has emerged as a powerful tool to enhance drug formulation development, offering the potential…
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AI-Assisted Diagnostics in Pediatric Dentistry: A Clinical Evaluation of Caries Detection Models
Dental caries remains one of the most prevalent chronic diseases among children globally, with early detection being critical to prevent progressive enamel and dentin damage. Pediatric dentistry faces a unique challenge in accurately diagnosing carious lesions…
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The Use of Machine Learning Algorithms to Detect Adverse Events in Real-Time from Clinical Databases
Adverse events (AEs) in clinical practice present significant challenges to patient safety, regulatory compliance, and healthcare costs. The rapid digitization of healthcare records and the emergence of electronic clinical databases have opened new avenues for leveraging…
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Leveraging AI-Based SAS Models to Predict Patient Dropout in Longitudinal Clinical Research
Patient retention is a critical determinant of data integrity and statistical power in longitudinal clinical research. High dropout rates can compromise study outcomes, inflate operational costs, and delay drug development timelines. Traditional methods to mitigate dropout,…
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Development of AI-Based Predictive Models for Vaccine Efficacy
Predicting vaccine efficacy has long posed challenges due to the complex interplay of host immunity, pathogen variability, and population-specific factors. This manuscript presents the foundations for developing Artificial Intelligence (AI)-based predictive models to estimate vaccine efficacy…
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Ethical Concerns in the Use of AI in Drug Side Effect Prediction
The integration of artificial intelligence (AI) in pharmacovigilance and drug side effect prediction has brought transformative advances in healthcare decision-making. By analyzing large datasets such as clinical trials, electronic health records, and pharmacological databases, AI models…
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Investigating AI-Designed Proteins for Drug Development
Advances in artificial intelligence (AI) have significantly influenced various domains in biotechnology, particularly in the design of synthetic proteins with potential applications in drug development. AI-based approaches, including machine learning algorithms and generative models, offer new…
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Development of AI-Powered Drug Repurposing Models
The process of discovering new therapeutic uses for existing drugs—known as drug repurposing—offers a cost-effective and time-saving alternative to traditional drug development. With the exponential growth in biomedical data, artificial intelligence (AI) models have emerged as…