Trends of Artificial Intelligence in Emergency and Critical Care Medicine

Dear Colleagues,

Summary: The Topic "Trends of Artificial Intelligence in Emergency and Critical Care Medicine" aims to explore the cutting-edge advancements and practical applications of AI in the fast-paced and high-stakes environments of emergency and critical care. This Topic seeks to serve as a comprehensive resource for healthcare professionals, researchers, and AI developers, highlighting the transformative potential of AI in enhancing patient care, streamlining hospital operations, and improving outcomes in critical situations.

Background: Emergency and critical care medicine is at the forefront of healthcare delivery, often dealing with life-or-death decisions under immense time pressure. The integration of AI presents an opportunity to augment clinical judgment, optimize resource allocation, and predict patient deterioration, thereby improving patient safety and clinical efficiency.

Aims:

1. Innovation Showcase: To present novel AI-driven technologies and algorithms designed to address specific challenges in emergency and critical care settings.
2. Clinical Integration: To discuss strategies for the successful implementation of AI in clinical workflows, focusing on interoperability with existing systems and user-centered design principles.
3. Data-Driven Insights: To examine the role of AI in analyzing complex medical data to predict patient outcomes, personalize treatment plans, and facilitate real-time decision-making.
4. Ethical Considerations: To explore the ethical implications of AI in emergency medicine, including issues of privacy, consent, and the potential for algorithmic bias.
5. Future Directions: To provide a forward-looking perspective on how AI might evolve and shape the future of emergency and critical care medicine.

Call for Contributions: We invite original research, review articles, and case studies that align with the aims of the Topic. Potential authors are encouraged to submit manuscripts that provide evidence-based insights, innovative solutions, and thoughtful discourse on the role of AI in emergency and critical care medicine. The editorial team will prioritize submissions that demonstrate a clear understanding of clinical needs, rigorous scientific methodology, and a commitment to improving patient care through AI.

Submission Guidelines: Authors should adhere to the journal's guidelines for manuscript preparation, ensuring that their work is both scientifically rigorous and accessible to a multidisciplinary audience. The Topic will undergo a thorough peer-review process to maintain the highest standards of academic integrity and clinical relevance.

Topic editors introduction:

Zhongheng Zhang's research program aims to enable precision treatment for critically ill adults, with the hypothesis that gene expression profiles generate clinical phenotypes and such networks could be determined by the integration of clinical and multi-omics data, such as those from RNA-seq and electronic healthcare records. Machine learning algorithms such as reinforcement learning and supervised and unsupervised learning can help to discover new knowledge and give more insights into precision medicine.

Dr. Hong Yucai is a distinguished medical professional with the title of Chief Physician and a supervisor for doctoral candidates at the Sir Run Run Shaw Hospital, affiliated with Zhejiang University School of Medicine. He holds a medical doctorate and has been recognized for his significant contributions to emergency medicine. With a long-standing commitment to the support and comprehensive treatment of critically ill patients and those suffering from severe trauma, Dr. Hong has been at the forefront of emergency and critical care medicine. He initiated the clinical application of and research into critical care ultrasound in 2004 and pioneered the PENLIGHT minimally invasive technique for the treatment of intractable aspiration pneumonia in 2006. His innovative spirit led him to explore standardized diagnosis and treatment protocols for critical illnesses based on daily checklists and goal-oriented approaches in 2015. Dr. Hong has also made significant strides in academia and professional associations. In 2017, he established the Asia Society of Emergency and Critical Care Medicine and launched the "Journal of Emergency and Critical Care Medicine", serving as its editor-in-chief. Additionally, he developed the SEED simulation teaching program for critical emergency conditions and has been instrumental in promoting these educational initiatives both within and outside of Zhejiang province. His leadership extends to various medical committees and societies, including serving as the Deputy Director of the Emergency Medicine Research Institute at Zhejiang University, the Vice Chairman of the Emergency Medicine Branch of the Chinese Medical Education Association, and a member of the Chinese Medical Doctor Association's Emergency Physicians Branch.

Dr. Wei Shao is from Nanjing University of Aeronautics and Astronautics. His main research areas are machine learning and medical image processing.

Dr. Zhongheng Zhang
Prof. Dr. Yucai Hong
Dr. Wei Shao
Topic Editors