American International Journal of Advanced Research and Development

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Artificial Intelligence-Based Diagnostic Support Systems in Healthcare

Author(s) Jeremy C. Wyatt
Country United Kingdom
Abstract Artificial intelligence has emerged as an important technological approach for strengthening diagnostic support in modern healthcare. The increasing volume of clinical records, medical images, laboratory information, physiological measurements, and other biomedical data has created opportunities for intelligent systems to assist healthcare professionals in detecting diseases, interpreting complex information, assessing clinical risks, and supporting diagnostic decision-making. This study examines artificial intelligence-based diagnostic support systems in healthcare, with particular emphasis on machine learning, deep learning, medical image analysis, clinical data interpretation, predictive analytics, and clinical decision support.
A qualitative descriptive and conceptual research design was adopted using secondary academic literature. The analysis indicates that AI-based diagnostic support systems can process large and heterogeneous datasets and identify patterns that may assist clinicians in disease detection and classification. These systems can support radiology, pathology, cardiology, oncology, laboratory medicine, and general clinical decision-making. However, their implementation is affected by challenges involving data quality, algorithmic bias, interpretability, privacy, cybersecurity, interoperability, model generalizability, clinical validation, and workflow integration.
The study concludes that AI-based diagnostic support systems can strengthen healthcare when they are developed using representative datasets, clinically validated algorithms, transparent analytical processes, and secure data infrastructures. Future research should emphasize explainable AI, multimodal clinical data integration, real-time diagnostic support, federated learning, human-AI collaboration, and prospective clinical validation.
Keywords Artificial Intelligence, Diagnostic Support Systems, Healthcare, Machine Learning, Deep Learning, Clinical Decision Support, Medical Diagnosis, Medical Imaging, Predictive Analytics, Healthcare Informatics.
Field Engineering
Published In Volume 5, Issue 3, May-June 2023
Published On 2023-05-26
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