Implementation of AI for predicting antibiotic resistance patterns: A hospital-based study
Year: 2025
Type: article
Abstract: The use of Artificial Intelligence (AI) to predict antibiotic resistance patterns in a hospital setting is of interest. By leveraging machine learning (ML) models, including Random Forest, Logistic Regression and Support Vector Machines, the study aimed to predict resistance based on patient demographics, microbial species and clinical data. The Random Forest model outperformed other models in terms of accuracy, precision and recall. Data shows the importance of integrating AI-driven tools into clinical workflows for improved antibiotic stewardship and patient outcomes. Despite challenges, AI presents a promising approach for combating antibiotic resistance in healthcare.
Source: Bioinformation
Authors: Anshuman Srivastava, Shailesh Tripathi, Ravikant R, Parth Jani, Mukul Singh, Amrit Podder, Mohammed Mustafa, Mukesh Kumar Patwa
Institutions: Rajendra Institute of Medical Sciences, Sankalchand Patel University, All India Institute of Medical Sciences, Rajkot, All India Institute of Medical Sciences Gorakhpur, Teerthanker Mahaveer University, Teerthanker Mahaveer Medical College & Research Centre, Mahaveer University, Prince Sattam Bin Abdulaziz University
Language: English
Subfield: Applied Microbiology and Biotechnology
Field: Immunology and Microbiology
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W4415944973