《Big Data Mining and Analytics》

作品数：288被引量：392H指数：9
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《Big Data Mining and Analytics》
主办单位：清华大学
最新期次：2024年4期更多>>
发文主题：LEARNINGMININGMACHINE_LEARNINGDATAANALYTICS更多>>
发文领域：自动化与计算机技术医药卫生文化科学理学更多>>
发文基金：国家自然科学基金高等学校学科创新引智计划广东省自然科学基金中国博士后科学基金更多>>
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SpaCCC:Large Language Model-Based Cell-Cell Communication Inference for Spatially Resolved Transcriptomic Data
《Big Data Mining and Analytics》2024年第4期1129-1147,共19页Boya Ji Xiaoqi Wang Debin Qiao Liwen Xu Shaoliang Peng 
supported by the National Natural Science Foundation of China-Science and Technology Development Fund(No.62361166662);the National Key R&D Program of China(Nos.2023YFC3503400 and 2022YFC3400400);the Key R&D Program of Hunan Province(Nos.2023GK2004,2023SK2059,and 2023SK2060);the Top 10 Technical Key Project in Hunan Province(No.2023GK1010);the Key Technologies R&D Program of Guangdong Province(No.2023B1111030004 to FFH);the Funds of State Key Laboratory of Chemo/Biosensing and Chemometrics,the National Supercomputing Center in Changsha(http://nscc.hnu.edu.cn/);Peng Cheng Lab.Graduate Research Innovation Project of Hunan Province(No.QL20230101).
Drawing parallels between linguistic constructs and cellular biology,Large Language Models(LLMs)have achieved success in diverse downstream applications for single-cell data analysis.However,to date,it still lacks met...
关键词：Large Language Models(LLM) spatial transcriptome data Cell-Cell Communications(CCCs) functional gene interaction networks unified latent space 
Large Language Models in Psychiatry:Current Applications,Limitations,and Future Scope
《Big Data Mining and Analytics》2024年第4期1148-1168,共21页Zhe Liu Yihang Bao Shuai Zeng Ruiyi Qian Miaohan Deng An Gu Jianye Li Weidi Wang Wenxiang Cai Wenhao Li Han Wang Dong Xu Guan Ning Lin 
supported by STI 2030—Major Projects(No.2022ZD0209100);the National Natural Science Foundation of China(Nos.81971292,82150610506,and 62372099);the Natural Science Foundation of Shanghai(No.21ZR1428600);The Medical-Engineering Cross Foundation of Shanghai Jiao Tong University(No.YG2022ZD026);the Jilin Scientific and Technological Development Program(Nos.20230401092YY and 20230201090GX);the Paul K.and Diane Shumaker Endowment Fund at University of Missouri,USA.
With the advancements in Artificial Intelligence(AI)technology,Large Language Models(LLMs)provide outstanding capabilities for natural language understanding and generation,enhancing various domains.In psychiatry,LLMs...
关键词：Artificial Intelligence(AI) Large Language Model(LLM) PSYCHIATRY medical application 
Transformer-Based Single-Cell Language Model:A Survey
《Big Data Mining and Analytics》2024年第4期1169-1186,共18页Wei Lan Guohang He Mingyang Liu Qingfeng Chen Junyue Cao Wei Peng 
supported by the National Natural Science Foundation of China(No.62072124);the Natural Science Foundation of Guangxi(No.2023JJG170006);the Natural Science and Technology Innovation Development Foundation of Guangxi University(No.2022BZRC009);the CAAI-Huawei MindSpore Open Fund(No.CAAIXSJLJJ-2022-022A);the Project of Guangxi Key Laboratory of Eye Health(No.GXYJK-202407);the Project of Guangxi Health Commission Eye and Related Diseases Artificial Intelligence Screen Technology Key Laboratory(No.GXYAI-202402).
The transformers have achieved significant accomplishments in the natural language processing as its outstanding parallel processing capabilities and highly flexible attention mechanism.In addition,increasing studies ...
关键词：language model TRANSFORMERS deep learning single-cell data 
KEXNet:A Knowledge-Enhanced Model for Improved Chest X-Ray Lesion Detection
《Big Data Mining and Analytics》2024年第4期1187-1198,共12页Quan Yan Junwen Duan Jianxin Wang 
supported by the National Key Research and Development Program of China(No.2021YFF1201200);the Science and Technology Major Project of Changsha(No.kh2402004).
Automated diagnosis of chest X-rays is pivotal in radiology,aiming to alleviate the workload of radiologists.Traditional methods primarily rely on visual features or label dependence,which is a limitation in detecting...
关键词：multi-label chest X-ray classification object detection knowledge graph learning 
TV-SAM:Increasing Zero-Shot Segmentation Performance on Multimodal Medical Images Using GPT-4 Generated Descriptive Prompts Without Human Annotation
《Big Data Mining and Analytics》2024年第4期1199-1211,共13页Zekun Jiang Dongjie Cheng Ziyuan Qin Jun Gao Qicheng Lao Abdullaev Bakhrom Ismoilovich Urazboev Gayrat Yuldashov Elyorbek Bekchanov Habibullo Defu Tang Linjing Wei Kang Li Le Zhang 
supported by the National Science and Technology Major Project(No.2021YFF1201200);Chinese National Science Foundation(No.62372316);Sichuan Science and Technology Program(Nos.2022YFS0048,2023YFG0126,and 2024YFHZ0091);1·3·5 Project for Disciplines of Excellence,West China Hospital,Sichuan University(No.ZYYC21004);Chongqing Technology Innovation and Application Development Project(No.CSTB2022TIAD-KPX0067).
This study presents a novel multimodal medical image zero-shot segmentation algorithm named the text-visual-prompt segment anything model(TV-SAM)without any manual annotations.The TV-SAM incorporates and integrates th...
关键词：large language model vision language model segment anything model medical image segmentation zero-shot segmentation GPT-4 
SeaConvNeXt:A Lightweight Two-Branch Network Architecture for Efficient Prediction of Specific IHC Proteins and Antigens on Hematoxylin and Eosin(H&E)Images
《Big Data Mining and Analytics》2024年第4期1212-1236,共25页Yuli Chen Guoping Chen Guoying Shi Yao Zhou Jiayang Bai Germán Corredor Cheng Lu Xiujuan Lei 
supported by the National Key R&D Program of China(No.2023YFC3402800);the National Natural Science Foundation of China(Nos.62371276,62272288,and 82272084);the Fundamental Research Funds for the Central Universities,Shaanxi Normal University(No.GK202302006).
Immunohistochemistry(IHC)is a vital technique for detecting specific proteins and antigens in tissue sections using antibodies,aiding in the analysis of tumor growth and metastasis.However,IHC is costly and time-consu...
关键词：Immunohistochemistry(IHC) Bi-stage Registration based on density Clustering(BiReC) automatic label generation SeaConvNeXt attention mechanism multi-level local and global features virtual IHC staning prediction 
MMAR-Net:A Multi-Stride and Multi-Resolution Affine Registration Network for CT Images
《Big Data Mining and Analytics》2024年第4期1287-1300,共14页Fu Zhou Fei Luo Ruoshan Kong Yi-Ping Phoebe Chen Feng Liu 
supported by the National Natural Science Foundation of China(No.62172309).
The evolution of lung lesions can be assessed by examining multiple CT screenings,which needs to align two CT images accurately.In this study,we propose a multi-stride and multi-resolution affine registration network,...
关键词：lung lesion affine registration multi-stride MULTI-RESOLUTION 
Distributed Heterogeneous Spiking Neural Network Simulator Using Sunway Accelerators
《Big Data Mining and Analytics》2024年第4期1301-1320,共20页Xuelei Li Zhichao Wang Yi Pan Jintao Meng Shengzhong Feng Yanjie Wei 
supported by the Key Research and Development Project of Guangdong Province(No.2021B0101310002);the National Key Research and Development Program of China(No.2021YFF1200104);the Strategic Priority CAS Project(No.XDB38050100);the National Natural Science Foundation of China(No.62272449);the Shenzhen Basic Research Fund(Nos.RCYX20200714114734194,JCYJ20210324102007021,and KQTD20200820113106007);the Open Fund of Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ)(No.GML-KF-22-13);the Shenzhen Key Laboratory of Intelligent Bioinformatics(No.ZDSYS20220422103800001).
Spiking Neural Network(SNN)simulation is very important for studying brain function and validating the hypotheses for neuroscience,and it can also be used in artificial intelligence.Recently,GPU-based simulators have ...
关键词：Spiking Neural Network(SNN)simulation Sunway accelerator random access Message Passing Interface(MPI)communication real-time simulation 
Coarse-to-Fine Approach:Automatic Delineation of Kidney Ultrasound Data
《Big Data Mining and Analytics》2024年第4期1321-1332,共12页Tao Peng Yiwen Ruan Yidong Gu Jiang Huang Caiyin Tang Jing Cai 
supported by the China Postdoctoral Science Foundation(No.2023M742568);the China Social Development Plan of Taizhou(No.TN202110)。
We present an automatic kidney segmentation method using ultrasound images.This method employs a coarse-to-fine approach to tackle the challenge of unclear and fuzzy boundaries.Four key innovations are introduced to e...
关键词：polyline segment technique artificial neural network explainable mathematical mapping formula ultrasound kidney segmentation 
Quick-MIMIC:A Multimodal Data Extraction Pipeline for MIMIC with Parallelization
《Big Data Mining and Analytics》2024年第4期1333-1346,共14页Yutao Dou Wei Li Yangtao Zheng Xiaojun Yao Huanxiang Liu Albert Y.Zomaya Shaoliang Peng 
supported by the National Natural Science Foundation of China-Science and Technology Development Fund(No.62361166662);the National Key R&D Program of China(Nos.2023YFC3503400 and 2022YFC3400400);the Key R&D Program of Hunan Province(Nos.2023GK2004,2023SK2059,and 2023SK2060);the Top 10 Technical Key Project in Hunan Province(No.2023GK1010);the Key Technologies R&D Program of Guangdong Province(No.2023B1111030004);the Funds of State Key Laboratory of Chemo/Biosensing and Chemometrics,the National Supercomputing Center in Changsha(http://nscc.hnu.edu.cn/),and Peng Cheng Lab.
Medical big data with artificial intelligence are vital in advancing digital medicine.However,the opaque and non-standardised nature embedded in most medical data extraction is prone to batch effects and has become a ...
关键词：MIMIC dataset data extraction pipeline data integration 
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