St. George's University

Acknowledging the use of human cadaveric tissues in research papers: Recommendations from anatomical journal editors

Joe Iwanaga, Vishram Singh, Aiji Ohtsuka et al.

2020 · 557 Zit.

Development of the Anatomical Quality Assessment (AQUA) Tool for the quality assessment of anatomical studies included in meta‐analyses and systematic reviews

Brandon Michael Henry, Krzysztof A. Tomaszewski, Piravin Kumar Ramakrishnan et al.

2016 · 270 Zit.

Standardized statement for the ethical use of human cadaveric tissues in anatomy research papers: Recommendations from <i>Anatomical Journal</i><scp>Editors‐in‐Chief</scp>

Joe Iwanaga, Vishram Singh, Sén Takeda et al.

2022 · 261 Zit.

Development of the Anatomical Quality Assurance (AQUA) Checklist: Guidelines for reporting original anatomical studies

Krzysztof A. Tomaszewski, Brandon Michael Henry, Piravin Kumar Ramakrishnan et al.

2016 · 168 Zit.

The role of an open artificial intelligence platform in modern neurosurgical education: a preliminary study

Umut Tan Sevgi, Gökberk Erol, Yücel Doğruel et al.

2023 · 80 Zit.

Consensus guidelines for the uniform reporting of study ethics in anatomical research within the framework of the anatomical quality assurance (AQUA) checklist

Brandon Michael Henry, Jens Vikse, Przemysław A. Pękala et al.

2018 · 49 Zit.

Ethical Use of Cadaveric Images in Anatomical Textbooks, Atlases, and Journals: A Consensus Response From Authors and Editors

Joe Iwanaga, Hee‐Jin Kim, Keiichi Akita et al.

2025 · 27 Zit.

The Roles of Artificial Intelligence in Teaching Anatomy: A Systematic Review

T. Joseph, Shelleen Gowrie, Michael J. Montalbano et al.

2025 · 26 Zit.

The Artificial Intelligence Revolution in Stroke Care: A Decade of Scientific Evidence in Review

Kareem El Naamani, Basel Musmar, Nithin Gupta et al.

2024 · 22 Zit.

Harnessing artificial intelligence to bridge the neurosurgery gap in low-income and middle-income countries

Wireko Andrew Awuah, Jacob Kalmanovich, Aashna Mehta et al.

2022 · 9 Zit.

Anatomical variants identified on chest computed tomography of 1000+ <scp>COVID</scp>‐19 patients from an open‐access dataset

Laphatrada Yurasakpong, Somluk Asuvapongpatana, Wattana Weerachatyanukul et al.

2022 · 9 Zit.

Ischemic heart disease-related mortality trends in the United States (1999–2020) and prediction using machine learning

Noman Khalid, Sabrina Clare Higgins, Muhammad Abdullah et al.

2025 · 4 Zit.

Strengths and Limitations of Using ChatGPT: A Preliminary Examination of Generative AI in Medical Education

Charlotte A. Taylor-Drigo, Anshul Kumar

2025 · 4 Zit.

Comparative Analysis of ChatGPT and Google Gemini in the Creation of Patient Education Materials for Acute Appendicitis, Cholecystitis, and Hydrocele

Thaïmye Joseph, Neysa Sanghavi, Shweta Kanyal et al.

2024 · 3 Zit.

The Role of Artificial Intelligence and Machine Learning in Cardiovascular Imaging and Diagnosis: Current Insights and Future Directions

Maria Gabriela Cerdas, Sucharitha Pandeti, Likhitha Reddy et al.

2024 · 3 Zit.