The Role of Artificial Intelligence in Antimicrobial Susceptibility Testing: Perceptions and Expectations of Medical Doctors of South Punjab, Pakistan.
Main Article Content
Abstract
Objective: To evaluate clinicians’ reliance on antimicrobial susceptibility testing (AST) and their perceptions, trust, and readiness to adopt artificial intelligence (AI)–enabled AST in clinical practice.
Methodology: A descriptive cross‑sectional study was conducted among 366 healthcare workers in South Punjab, Pa-kistan. Data on reliance, perceptions of AI‑enabled AST, trust, implementation, and concerns were analyzed using chi‑square (χ ²) tests.
Results: Demographic analysis showed that 51.0% of participants had less than five years of clinical experience, with medical officers comprising 48.9% (P<0.001). Females predominated (59.2% vs. 40.7%; P<0.01). Most respondents practiced in Lahore (37.7%) or Multan (33.0%; P<0.001), with surgery (34.4%) and pediatrics (22.9%) being the leading departments (P<0.001). Reliance on AST was high: 69.6% strongly agreed and 21.5% agreed that AST guided prescrib-ing decisions, though 72.9% noted delays limited optimal selection. Interpretation was seen as judgment‑dependent (41.5% strongly agree). Perceptions of AI were highly positive: 84.4% strongly agreed AI could improve accuracy, 76.2% reduce inappropriate use, and 82.2% aid earlier decisions. Trust and willingness to adopt were strong (95.9% trusted validated AI; 93.4% were willing to use it alongside conventional AST). Concerns included transparency (35.2%), bias (59.8%), unclear legal responsibility (78.9%), and infrastructure (75.9%). Most supported training (81.1%) and regu-latory oversight (71.8%). Significant variation was observed across responses (P<0.001).
Conclusion: Clinicians view AI‑enabled AST as a promising complementary tool, contingent on validation, governance, training, and integration.
Keywords: Antimicrobial susceptibility testing; Artificial intelligence; Antimicrobial resistance; Clinical decision support; Stewardship; Healthcare workers.
Downloads
Article Details

This work is licensed under a Creative Commons Attribution 4.0 International License.
Journal of Muhammad Medical College (J Muhammad Med Coll) belief that all researches are basically conducted for the benefit of humanity. Research is the product of an investment by society and consequently its fruits should be returned in a transparent fashion to all humankind without any discrimination.
Journal of Muhammad Medical College is an open access journal which means that all content is freely available without charge to users or / institution. When used non-commercially all users are allowed to read, download, copy, distribute, print, search, or link to full text articles in this journal without asking prior permission from the publisher or author as long as original author(s) are acknowledged.
Journal of Muhammad Medical College operate under Creative Common License CC-BY-SA that allow reproduction of articles free of charge, for non-commercial use only and with the appropriate citation information. All authors publishing with Journal of Muhammad Medical College accept these as the terms of publication.

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License