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Perception of artificial intelligence in pathology: Insight from clinical laboratory professionals in a tertiary care hospital in Pakistan


Article Information

Title: Perception of artificial intelligence in pathology: Insight from clinical laboratory professionals in a tertiary care hospital in Pakistan

Authors: Rida Akhtar, Armaghana Qamar Khan, Mehreen Mushtaq, Asma Khattak, Salma Iltaf, Soffia Khursheed

Journal: Pakistan Journal of Pathology

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30
Y 2021-07-01 2022-06-30
Y 2020-07-01 2021-06-30
Y 1900-01-01 2005-06-30

Publisher: Pakistan Association of Pathologists

Country: Pakistan

Year: 2025

Volume: 36

Issue: 3

Language: en

DOI: 10.55629/pakjpathol.v36i3.940

Categories

Abstract

Objective: Our study aims to assess knowledge and perception about artificial intelligence among clinical laboratories professionals in a tertiary care hospital setting.
Material and Methods: A descriptive cross-sectional study was carried out for one month from 2 July 2024 to 2 August 2024 using consecutive sampling with the help of a pre-designed questionnaire that contained six sections: demographics, knowledge of AI in pathology, attitudes towards AI in pathology, perceived benefits and barriers, training and education, and open-ended questions. The study population included doctors, technical staff, laboratory attendants, and technicians working in the PIMS pathology laboratory, a tertiary care setting. A sample size of 100 participants was selected. Both male and female participants were included, while individuals unwilling to participate were excluded from the study. Frequencies were calculated and tables with figures generated for presentation.
Results:  A total of n = 89 participants completed the survey, with a mean age of 36.8 years (SD ± 7.9). Most were female (75.3%) and pathologists (65.2%). Overall, 93.7% reported some familiarity with AI, though only 34.1% were slightly familiar. More than half agreed that AI could improve diagnostic accuracy (53.9%) and efficiency (60.2%), while concerns included reliability (54.5%) and data privacy (30.7%).
Conclusion: The study suggests that there is a need to develop education and training programs to address this knowledge gap as well as concerns regarding the use of AI in pathology.
Keywords: Artificial Intelligence, Clinical Laboratory Personnel, Education, Medical, Pathology, Tertiary caresetting.


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