
Zhaomin Yao
Northeast University, College of Medicine and Biological Information Engineering; General Hospital of Northern Theater Command, Department of Nuclear Medicine
Zhaomin Yao graduated from Northeast University, China, with a bachelor's degree in 2016 and a master's degree in 2019. In the following years, he developed a voice electronic medical record system for the respiratory department of Zhongshan Hospital Affiliated to Fudan University. He has been studying for his doctorate since 2021 at Northeast University, China. Dr. Yao’s current research focuses on building diagnostic and prognostic models for medical images and related omics data, especially for the early diagnosis and staging of Alzheimer's disease based on PET/MRI images. His goal is to develop more effective imaging methods and to help interpret imaging results in a variety of neurological conditions by building interpretable features.

Xin Feng
Jilin Institute of Chemical Technology
Dr. Xin Feng received her PhD from the School of Computer Science at Jilin University in June 2019. She has since been a postdoctoral fellow at the School of Public Health at Jilin University since December 2019. Currently, she serves as a lecturer at the School of Science of the Jilin University of Chemical Technology in the Department of Data Science and Big Data. Her expertise includes deep learning algorithms and classical machine learning algorithms for big biomedical data. These algorithms will enable the use of modelling in heterogeneous bionomics, medical case and literature mining, and medical multimodal image modelling. Research directions are as follows: 1. The application of big data analysis technology in the life sciences; 2. The design and development of algorithms for precision medicine and complex diseases; 3. Deep learning-based methods for processing intelligent data; 4. Data mining, big data, cloud computing, and big data analytics for intelligent manufacturing.
Nuclear medicine is a medical imaging procedure that uses a specific imaging agent to locate a certain tissue or organ for disease diagnosis. It mainly displays information that is not visible to the naked eye, such as blood flow, function, and tissue or organ metabolism. With nuclear medicine imaging modalities such as PET/CT and PET/MR, more accurate and detailed imaging and data collection are possible for major diseases in neurology, oncology, and cardiology. In this way, patients can receive treatment earlier.
This Methods Collection covers a broad range of fields, including basic research, preclinical and clinical research, and translational research. Of particular interest are artificial intelligence-based analyses of nuclear medical images. Topics covered may include the most recent developments in the following areas:
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A Dual-Database Bibliometric Analysis of Radiotherapy-Related Skin Injury: Knowledge Structure and Emerging Trends
Xiaodan Wu1
1Department of Nuclear Medicine, General Hospital of Northern Theater Command, Shenyang, Liaoning 110016, China; College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, Liaoning 110167, China