765 citations · 2.1k across the 63 of their papers we have counts for
64 papers
PolicyGPT: Automated Analysis of Privacy Policies with Large Language Models
Chenhao Tang, Zhengliang Liu, Chong Ma +8
Privacy policies serve as the primary conduit through which online service providers inform users about their data collection and usage procedures. However, in a bid to be comprehe…
MA-SAM: Modality-agnostic SAM Adaptation for 3D Medical Image Segmentation
Cheng Chen, Juzheng Miao, Dufan Wu +10
The Segment Anything Model (SAM), a foundation model for general image segmentation, has demonstrated impressive zero-shot performance across numerous natural image segmentation ta…
Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges
Fei Dou, Jin Ye, Geng Yuan +22
Artificial General Intelligence (AGI), possessing the capacity to comprehend, learn, and execute tasks with human cognitive abilities, engenders significant anticipation and intrig…
Chat2Brain: A Method for Mapping Open-Ended Semantic Queries to Brain Activation Maps
Yaonai Wei, Tuo Zhang, Han Zhang +10
Over decades, neuroscience has accumulated a wealth of research results in the text modality that can be used to explore cognitive processes. Meta-analysis is a typical method that…
Artificial General Intelligence for Radiation Oncology
Chenbin Liu, Zhengliang Liu, Jason Holmes +14
The emergence of artificial general intelligence (AGI) is transforming radiation oncology. As prominent vanguards of AGI, large language models (LLMs) such as GPT-4 and PaLM 2 can…
MKRAG: Medical Knowledge Retrieval Augmented Generation for Medical Question Answering
Yucheng Shi, Shaochen Xu, Tianze Yang +5
Large Language Models (LLMs), although powerful in general domains, often perform poorly on domain-specific tasks such as medical question answering (QA). In addition, LLMs tend to…
MediViSTA: Medical Video Segmentation via Temporal Fusion SAM Adaptation for Echocardiography
Sekeun Kim, Pengfei Jin, Cheng Chen +9
Despite achieving impressive results in general-purpose semantic segmentation with strong generalization on natural images, the Segment Anything Model (SAM) has shown less precisio…
RadOnc-GPT: A Large Language Model for Radiation Oncology
Zhengliang Liu, Peilong Wang, Yiwei Li +12
This paper presents RadOnc-GPT, a large language model specialized for radiation oncology through advanced tuning methods. RadOnc-GPT was finetuned on a large dataset of radiation…
Radiology-Llama2: Best-in-Class Large Language Model for Radiology
Zhengliang Liu, Yiwei Li, Peng Shu +18
This paper introduces Radiology-Llama2, a large language model specialized for radiology through a process known as instruction tuning. Radiology-Llama2 is based on the Llama2 arch…
Robust Core-Periphery Constrained Transformer for Domain Adaptation
Xiaowei Yu, Zeyu Zhang, Dajiang Zhu +1
Unsupervised domain adaptation (UDA) aims to learn transferable representation across domains. Recently a few UDA works have successfully applied Transformer-based methods and achi…
Hierarchical Semantic Tree Concept Whitening for Interpretable Image Classification
Haixing Dai, Lu Zhang, Lin Zhao +9
With the popularity of deep neural networks (DNNs), model interpretability is becoming a critical concern. Many approaches have been developed to tackle the problem through post-ho…
Exploring Multimodal Approaches for Alzheimer's Disease Detection Using Patient Speech Transcript and Audio Data
Hongmin Cai, Xiaoke Huang, Zhengliang Liu +8
Alzheimer's disease (AD) is a common form of dementia that severely impacts patient health. As AD impairs the patient's language understanding and expression ability, the speech of…
Segment Anything Model (SAM) for Radiation Oncology
Lian Zhang, Zhengliang Liu, Lu Zhang +10
In this study, we evaluate the performance of the Segment Anything Model (SAM) in clinical radiotherapy. Our results indicate that SAM's 'segment anything' mode can achieve clinica…
Identification of Causal Relationship between Amyloid-beta Accumulation and Alzheimer's Disease Progression via Counterfactual Inference
Haixing Dai, Mengxuan Hu, Qing Li +12
Alzheimer's disease (AD) is a neurodegenerative disorder that is beginning with amyloidosis, followed by neuronal loss and deterioration in structure, function, and cognition. The…
Review of Large Vision Models and Visual Prompt Engineering
Jiaqi Wang, Zhengliang Liu, Lin Zhao +18
Visual prompt engineering is a fundamental technology in the field of visual and image Artificial General Intelligence, serving as a key component for achieving zero-shot capabilit…
Evaluating Large Language Models for Radiology Natural Language Processing
Zhengliang Liu, Tianyang Zhong, Yiwei Li +43
The rise of large language models (LLMs) has marked a pivotal shift in the field of natural language processing (NLP). LLMs have revolutionized a multitude of domains, and they hav…
SAMAug: Point Prompt Augmentation for Segment Anything Model
Haixing Dai, Chong Ma, Zhiling Yan +14
This paper introduces SAMAug, a novel visual point augmentation method for the Segment Anything Model (SAM) that enhances interactive image segmentation performance. SAMAug generat…
Exploring New Frontiers in Agricultural NLP: Investigating the Potential of Large Language Models for Food Applications
Saed Rezayi, Zhengliang Liu, Zihao Wu +8
This paper explores new frontiers in agricultural natural language processing by investigating the effectiveness of using food-related text corpora for pretraining transformer-base…
AD-AutoGPT: An Autonomous GPT for Alzheimer's Disease Infodemiology
Haixing Dai, Yiwei Li, Zhengliang Liu +14
In this pioneering study, inspired by AutoGPT, the state-of-the-art open-source application based on the GPT-4 large language model, we develop a novel tool called AD-AutoGPT which…
Radiology-GPT: A Large Language Model for Radiology
Zhengliang Liu, Aoxiao Zhong, Yiwei Li +17
We introduce Radiology-GPT, a large language model for radiology. Using an instruction tuning approach on an extensive dataset of radiology domain knowledge, Radiology-GPT demonstr…
Artificial General Intelligence for Medical Imaging Analysis
Xiang Li, Lin Zhao, Lu Zhang +16
Large-scale Artificial General Intelligence (AGI) models, including Large Language Models (LLMs) such as ChatGPT/GPT-4, have achieved unprecedented success in a variety of general…
Beam mask and sliding window-facilitated deep learning-based accurate and efficient dose prediction for pencil beam scanning proton therapy
Lian Zhang, Jason M. Holmes, Zhengliang Liu +12
Purpose: To develop a DL-based PBSPT dose prediction workflow with high accuracy and balanced complexity to support on-line adaptive proton therapy clinical decision and subsequent…
SAM for Poultry Science
Xiao Yang, Haixing Dai, Zihao Wu +7
In recent years, the agricultural industry has witnessed significant advancements in artificial intelligence (AI), particularly with the development of large-scale foundational mod…
Learning Better Contrastive View from Radiologist's Gaze
Sheng Wang, Zixu Zhuang, Xi Ouyang +6
Recent self-supervised contrastive learning methods greatly benefit from the Siamese structure that aims to minimizing distances between positive pairs. These methods usually apply…