The role of artificial intelligence in laboratory medicine: Enhancing diagnostic accuracy and efficiency

Ola Yousef Fadan; Abdullah Saad Abunaian; Mohammed Amaash Alanizi; Ahlam Nazeh Alenezi; Mohammed Rashed Al Otaibi; Musab Abdulgader Alfares; Khalid Abdulrahman Alsharif; Motaeb Saqer Alenazi; Zainab Ali Alqarni; Ahmed Mufleh Alenazi; Abdulaziz Radi Alanazi; Bushra Mana Alshammari; Dima Ahmed Alharbi; Mohammed Abdullah Shujaa

doi:10.53730/ijhs.v3nS1.15015

Authors

Ola Yousef Fadan KSA, National Guard Health Affairs
Abdullah Saad Abunaian KSA, National Guard Health Affairs
Mohammed Amaash Alanizi KSA, National Guard Health Affairs
Ahlam Nazeh Alenezi KSA, National Guard Health Affairs
Mohammed Rashed Al Otaibi KSA, National Guard Health Affairs
Musab Abdulgader Alfares KSA, National Guard Health Affairs
Khalid Abdulrahman Alsharif KSA, National Guard Health Affairs
Motaeb Saqer Alenazi KSA, National Guard Health Affairs
Zainab Ali Alqarni KSA, National Guard Health Affairs
Ahmed Mufleh Alenazi KSA, National Guard Health Affairs
Abdulaziz Radi Alanazi KSA, National Guard Health Affairs
Bushra Mana Alshammari KSA, National Guard Health Affairs
Dima Ahmed Alharbi KSA, National Guard Health Affairs
Mohammed Abdullah Shujaa KSA, National Guard Health Affairs

Keywords:

Precision Medicine, Artificial Intelligence, Machine Learning, Electronic Health Records, Data-Driven Healthcare

Abstract

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.

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