15 citations · 16 across the 10 of their papers we have counts for
10 papers
Quantifying the Dynamics of Harm Caused by Retracted Research
Yunyou Huang, Jiahui Zhao, Dandan Cui +10
Despite enormous efforts devoted to understand the characteristics and impacts of retracted papers, little is known about the mechanisms underlying the dynamics of their harm and t…
Establishing Rigorous and Cost-effective Clinical Trials for Artificial Intelligence Models
Wanling Gao, Yunyou Huang, Dandan Cui +22
A profound gap persists between artificial intelligence (AI) and clinical practice in medicine, primarily due to the lack of rigorous and cost-effective evaluation methodologies. S…
AI.vs.Clinician: Unveiling Intricate Interactions Between AI and Clinicians through an Open-Access Database
Wanling Gao, Yuan Liu, Zhuoming Yu +21
Artificial Intelligence (AI) plays a crucial role in medical field and has the potential to revolutionize healthcare practices. However, the success of AI models and their impacts…
Evaluatology: The Science and Engineering of Evaluation
Jianfeng Zhan, Lei Wang, Wanling Gao +10
Evaluation is a crucial aspect of human existence and plays a vital role in various fields. However, it is often approached in an empirical and ad-hoc manner, lacking consensus on…
OpenClinicalAI: An Open and Dynamic Model for Alzheimer's Disease Diagnosis
Yunyou Huang, Xiaoshuang Liang, Xiangjiang Lu +9
Although Alzheimer's disease (AD) cannot be reversed or cured, timely diagnosis can significantly reduce the burden of treatment and care. Current research on AD diagnosis models u…
OpenAPMax: Abnormal Patterns-based Model for Real-World Alzheimer's Disease Diagnosis
Yunyou Huang, Xianglong Guan, Xiangjiang Lu +8
Alzheimer's disease (AD) cannot be reversed, but early diagnosis will significantly benefit patients' medical treatment and care. In recent works, AD diagnosis has the primary assu…
OpenClinicalAI: enabling AI to diagnose diseases in real-world clinical settings
Yunyou Huang, Nana Wang, Suqin Tang +10
This paper quantitatively reveals the state-of-the-art and state-of-the-practice AI systems only achieve acceptable performance on the stringent conditions that all categories of s…
A Semantic-based Medical Image Fusion Approach
Fanda Fan, Yunyou Huang, Lei Wang +4
It is necessary for clinicians to comprehensively analyze patient information from different sources. Medical image fusion is a promising approach to providing overall information…
A new direction to promote the implementation of artificial intelligence in natural clinical settings
Yunyou Huang, Zhifei Zhang, Nana Wang +4
Artificial intelligence (AI) researchers claim that they have made great `achievements' in clinical realms. However, clinicians point out the so-called `achievements' have no abili…
Landscape of Big Medical Data: A Pragmatic Survey on Prioritized Tasks
Zhifei Zhang, Wanling Gao, Fan Zhang +13
Big medical data poses great challenges to life scientists, clinicians, computer scientists, and engineers. In this paper, a group of life scientists, clinicians, computer scientis…