Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
@article{199743,
author = {Aman Liladhar Giripunje and Rakhi Krushna Tonde and Harshali Surendra Galole and Rutvika Y. Barudwale and Achal Harinayan Yelane and Dr. Nitin H. Indurwade},
title = {A Survey on aspects of people on AI and Automation in Healthcare},
journal = {International Journal of Innovative Research in Technology},
year = {2026},
volume = {12},
number = {11},
pages = {14864-14866},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=199743},
abstract = {Artificial intelligence (AI) is rapidly transforming healthcare by enabling systems to perform complex cognitive tasks such as decision-making, pattern recognition, and predictive analysis. This study examines public knowledge, attitude, and perception of AI and automation in healthcare through a questionnaire-based survey of 141 participants in Wardha District. AI technologies, including Machine Learning, and cloud – based system, are recognized for improving diagnostic accuracy, Enhancing clinical decision making, streamlining administrative workflow, and addressing healthcare workforce shortage.
Findings reveal a generally positive perception, with most participants acknowledging AI’s role in disease detection, treatment efficiency, patient monitoring outcomes. Awareness of tools such as robotics surgery, virtual health assistants, and predictive analytics was moderate to high among respondents. However, concern remain regarding data privacy, ethical implication, and potential job displacement, emphasizing the need for responsible and transparent implementation. Increased exposure to AI technologies has contributed to a shift from skepticism to cautious optimism.
Overall, AI is viewed as a valuable asset in modern healthcare, though its acceptance depends on trust, transparency, accessibility, and ethical governance framework.},
keywords = {Artificial Intelligence, Healthcare Automation, Machine learning, public perception, Ethical concern, Diagnostic Accuracy, Data privacy.},
month = {April},
}
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