Year: 2023
Type: article
Abstract: Medical Artificial Intelligence (MedAI) harnesses the power of medical research through AI algorithms and vast data to address healthcare challenges. The security, integrity, and credibility of MedAI tools are paramount, because human lives are at stake. Predatory research, in a culture of “publish or perish,” is exploiting the “pay for publish” model to infiltrate he research literature repositories. Although, it is challenging to measure the actual predatory research induced data pollution and patient harm, our work shows that the breached integrity of MedAI inputs is a serious threat to trust the MedAI output. We review a wide range of research literature discussing the threats of data pollution in the research literature, feasible attacks impacting MedAI solutions, research literature-based tools, and influence on healthcare. Our contribution lies in presenting a comprehensive literature review, addressing the gap of predatory research vulnerabilities affecting MedAI solutions, and helping to develop robust MedAI solutions in the future.
Source: ACM Computing Surveys
DOI: 10.1145/3592597
Authors: Shalini Saini, Nitesh Saxena
Institution: Texas A&M University
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4365447235