Related Experiment Video
Updated: Jan 20, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
Published on: July 11, 2025
Preserving scientific integrity in academic publishing: Navigating artificial intelligence, journal policies, and the
Mahmut Enes Kayaalp1, Stefano Zaffagnini2, Michael A Mont3
1Department of Orthopaedics and Traumatology University of Health Sciences, Istanbul Fatih Sultan Mehmet Training and Research Hospital Istanbul Turkey.
None:
The integration of artificial intelligence (AI), the rise of mega-journals, and the manipulation of impact factors present challenges to scientific integrity. These trends threaten the core principles of objectivity, reproducibility, and transparency. This editorial highlights two categories of threats: (1) external pressures, such as AI misuse and metric-driven publishing models, and (2) internal systemic flaws, including the 'publish or perish' culture and methodological fragility. Mega-journals, characterized by high-volume publishing and broad interdisciplinary scopes, improve accessibility and accelerate dissemination. However, the emphasis on publication volume might weaken the rigor of peer review. To navigate these challenges, the authors propose a balanced approach that harnesses innovation without compromising scientific integrity. Proposed solutions include mandating AI transparency through frameworks like CONSORT-AI, and redefining impact metrics to emphasize reproducibility, mentorship, and societal impact alongside citations. Scientific journals should promote career opportunities less on publication quantity and more on quality. Global cooperation, via initiatives like the San Francisco Declaration on Research Assessment (DORA) and the Committee on Publication Ethics (COPE), is essential to standardize ethics and address resource disparities. This editorial proposes solutions for researchers, journals, and policymakers to realign academic incentives and uphold the ethical foundation of the science. By fostering transparency, accountability, and equity, the scientific community can preserve its ethical foundations while embracing transformative tools-ultimately advancing knowledge and serving society.
Level Of Evidence:
Level V.
Related Concept Videos
05:33Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:49Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images
Water Quality Analysis via Indicator Organisms
Demonstrating Author: Luisa Ikner
Water quality analysis monitors anthropogenic influences such as pollutants, nutrients, pathogens, and any other constituent that can impact the water’s integrity as a resource. Fecal contamination contributes microbial pathogens that threaten plant, animal, and human health with disease or illness. Increasing water demands and strict quality standards require that...
06:37Artificial Intelligence-Based System for Detecting Attention Levels in Students
09:11Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence
07:09Integrating Visual Psychophysical Assays within a Y-Maze to Isolate the Role that Visual Features Play in Navigational Decisions

