Abstract
Antimicrobial resistance (AMR) presents a formidable global health challenge, necessitating innovative strategies to optimize antibiotic usage. This chapter delves into the integration of Artificial Intelligence (AI) within Antimicrobial Stewardship Programs (ASPs) to enhance clinical decision-making and combat AMR effectively. It outlines the foundational concepts of antimicrobial stewardship (AS), emphasizing its critical role in mitigating AMR and improving patient outcomes. The chapter explores the application of AI technologies, including machine learning, natural language processing, and clinical decision support systems, in analyzing electronic health records and predicting resistance patterns. These AI-driven approaches facilitate personalized antibiotic prescribing, real-time surveillance, and proactive intervention strategies. Additionally, the chapter addresses the implementation challenges and future directions of AI-enabled ASPs, underscoring the importance of interdisciplinary collaboration and continuous innovation. By harnessing the potential of AI, healthcare providers can significantly advance antimicrobial stewardship, ensuring the sustainable use of antibiotics and safeguarding public health for future generations.
| Original language | English |
|---|---|
| Title of host publication | Artificial Intelligence in Managing Antimicrobial Resistance |
| Publisher | CRC Press |
| Pages | 91-110 |
| Number of pages | 20 |
| ISBN (Electronic) | 9781040411667 |
| ISBN (Print) | 9781032812458 |
| State | Published - 01 01 2025 |
Bibliographical note
Publisher Copyright:© 2025 Ramendra Pati Pandey, Chung-Ming Chang and V. Samuel Raj.
