Systematic Review
Systematic reviews synthesize existing research on a specific topic to provide a comprehensive and unbiased overview, guiding future research and informing practice. Current research focuses on applying systematic review methodologies across diverse fields, leveraging machine learning and large language models to automate tasks like literature searching, data extraction, and analysis, particularly in areas like healthcare, finance, and AI development. This approach enhances the efficiency and scalability of evidence synthesis, leading to more robust conclusions and improved decision-making in various scientific and practical domains.
Papers
AI-based Reconstruction for Fast MRI -- A Systematic Review and Meta-analysis
Yutong Chen, Carola-Bibiane Schönlieb, Pietro Liò, Tim Leiner, Pier Luigi Dragotti, Ge Wang, Daniel Rueckert, David Firmin, Guang Yang
Explainable Artificial Intelligence Methods in Combating Pandemics: A Systematic Review
Felipe Giuste, Wenqi Shi, Yuanda Zhu, Tarun Naren, Monica Isgut, Ying Sha, Li Tong, Mitali Gupte, May D. Wang