31 citations · 62 across the 20 of their papers we have counts for
20 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…
Younger: The First Dataset for Artificial Intelligence-Generated Neural Network Architecture
Zhengxin Yang, Wanling Gao, Luzhou Peng +3
Designing and optimizing neural network architectures typically requires extensive expertise, starting with handcrafted designs and then manual or automated refinement. This depend…
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…
High fusion computers: The IoTs, edges, data centers, and humans-in-the-loop as a computer
Wanling Gao, Lei Wang, Mingyu Chen +13
Emerging and future applications rely heavily upon systems consisting of Internet of Things (IoT), edges, data centers, and humans-in-the-loop. Significantly different from warehou…
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…
FLBench: A Benchmark Suite for Federated Learning
Yuan Liang, Yange Guo, Yanxia Gong +3
Federated learning is a new machine learning paradigm. The goal is to build a machine learning model from the data sets distributed on multiple devices so-called an isolated data i…
AIBench Training: Balanced Industry-Standard AI Training Benchmarking
Fei Tang, Wanling Gao, Jianfeng Zhan +30
Earlier-stage evaluations of a new AI architecture/system need affordable benchmarks. Only using a few AI component benchmarks like MLPerfalone in the other stages may lead to misl…
AIBench: An Agile Domain-specific Benchmarking Methodology and an AI Benchmark Suite
Wanling Gao, Fei Tang, Jianfeng Zhan +31
Domain-specific software and hardware co-design is encouraging as it is much easier to achieve efficiency for fewer tasks. Agile domain-specific benchmarking speeds up the process…
Edge AIBench: Towards Comprehensive End-to-end Edge Computing Benchmarking
Tianshu Hao, Yunyou Huang, Xu Wen +8
In edge computing scenarios, the distribution of data and collaboration of workloads on different layers are serious concerns for performance, privacy, and security issues. So for…
AIBench: An Industry Standard Internet Service AI Benchmark Suite
Wanling Gao, Fei Tang, Lei Wang +22
Today's Internet Services are undergoing fundamental changes and shifting to an intelligent computing era where AI is widely employed to augment services. In this context, many inn…
LoadCNN: A Low Training Cost Deep Learning Model for Day-Ahead Individual Residential Load Forecasting
Yunyou Huang, Nana Wang, Wanling Gao +4
Accurate day-ahead individual residential load forecasting is of great importance to various applications of smart grid on day-ahead market. Deep learning, as a powerful machine le…
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…
Clustering Residential Electricity Load Curves via Community Detection in Network
Yunyou Huang, Jianfeng Zhan, Nana Wang +3
Performing analytic of household load curves (LCs) has significant value in predicting individual electricity consumption patterns, and hence facilitate developing demand-response…
A veracity preserving model for synthesizing scalable electricity load profiles
Yunyou Huang, Jianfeng Zhan, Chunjie Luo +5
Electricity users are the major players of the electric systems, and electricity consumption is growing at an extraordinary rate. The research on electricity consumption behaviors…