The role of artificial intelligence in laboratory medicine: Enhancing diagnostic accuracy and efficiency - Fadan, Ola Yousef; Abunaian, Abdullah Saad; Alanizi, Mohammed Amaash; Alenezi, Ahlam Nazeh; Al Otaibi, Mohammed Rashed; Alfares, Musab Abdulgader; Alsharif, Khalid Abdulrahman; Alenazi, Motaeb Saqer; Alqarni, Zainab Ali; Alenazi, Ahmed Mufleh; Alanazi, Abdulaziz Radi; Alshammari, Bushra Mana; et al. (International journal of health sciences, 2019)
Background _ Precision medicine represents a significant shift in healthcare, moving away from traditional symptom-based approaches to a more individualized strategy that leverages advanced diagnostics. By focusing on early interventions and personalized therapies, precision medicine seeks to improve patient outcomes and optimize healthcare costs. The approach relies on comprehensive patient data analysis to differentiate between healthy and ill individuals, ultimately leading to a better understanding of biological markers related to health changes. Aim of Work – The primary aim of this research is to explore various artificial intelligence (AI) and machine learning (ML) solutions and methodologies that can enhance the implementation of precision medicine. The goal is to facilitate a data-driven healthcare model that improves clinical decision-making and patient outcomes. Methods – The research involves a thorough examination of current AI and ML technologies, analytic tools, and databases that can integrate diverse data sources, such as electronic health records (EHRs), clinical data, and public health information. The study also addresses the ethical and societal implications surrounding healthcare data privacy and security. Results – The findings suggest that advancements in AI and ML can significantly improve the categorization of patients and enhance the understanding of disease progression.