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The Large Language Models on Biomedical Data Analysis: A Survey

IEEE Journal of Biomedical and Health Informatics 2025年第6期29卷 4486-4497页

作者： Lan, Wei Tang, Zhentao Liu, Mingyang Chen, Qingfeng Peng, Wei Chen, Yi-Ping Phoebe Pan, Yi Guangxi University School of Computer Electronic and Information Nanning530004 China Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650500 China La Trobe University Department of Computer Science and Information Technology MelbourneVIC3086 Australia Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

With the rapid development of Large Language Model (LLM) technology, it has become an indispensable force in biomedical data analysis research. However, biomedical researchers currently have limited knowledge about LLM. Therefore, there is an urgent need for a summary of LLM applications in biomedical data analysis. Herein, we propose this review by summarizing the latest research work on LLM in biomedicine. In this review, LLM techniques are first outlined. We then discuss biomedical datasets and frameworks for biomedical data analysis, followed by a detailed analysis of LLM applications in genomics, proteomics, transcriptomics, radiomics, single-cell analysis, medical texts and drug discovery. Finally, the challenges of LLM in biomedical data analysis are discussed. In summary, this review is intended for researchers interested in LLM technology and aims to help them understand and apply LLM in biomedical data analysis research. © 2013 IEEE.

关键词： Data consistency

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Enhancement of charging performance of quantum battery via quantum coherence of bath

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Chinese Physics B 2023年第1期32卷 161-171页

作者：于文莉张允李海魏广芬韩丽萍田峰邹建 School of Computer Science and Technology Shandong Technology and Business UniversityYantai 264005China School of Information and Electronic Engineering Shandong Technology and Business UniversityYantai 264005China School of Science Tianjin University of TechnologyTianjin 300384China School of Physics Beijing Institute of TechnologyBeijing 100081China

An open quantum battery(QB)model of a single qubit system charging in a coherent auxiliary bath(CAB)consisting of a series of independent coherent ancillae is *** to the collision charging protocol we derive a quantum master equation and obtain the analytical solution of QB in a steady *** find that the full charging capacity(or the maximal extractable work(MEW))of QB,in the weak QB-ancilla coupling limit,is positively correlated with the coherence magnitude of *** with the numerical simulations we compare with the charging properties of QB at finite coupling strength,such as the MEW,average charging power and the charging efficiency,when considering the bath to be a thermal auxiliary bath(TAB)and a CAB,*** find that when the QB with CAB,in the weak coupling regime,is in fully charging,both its capacity and charging efficiency can go beyond its classical counterpart,and they increase with the increase of coherence magnitude of *** addition,the MEW of QB in the regime of relative strong coupling and strong coherent magnitude shows the oscillatory behavior with the charging time increasing,and the first peak value can even be larger than the full charging MEW of *** also leads to a much larger average charging power than that of QB with TAB in a short-time charging *** features suggest that with the help of quantum coherence of CAB it becomes feasible to switch the charging schemes between the long-time slow charging protocol with large capacity and high efficiency and the short-time rapid charging protocol with highly charging power only by adjusting the coupling strength of *** work clearly demonstrates that the quantum coherence of bath can not only serve as the role of“fuel”of QB to be utilized to improve the QB's charging performance but also provide an alternative way to integrate the different charging protocols into a single QB.

关键词： quantum battery quantum coherence maximal extractable work charging power

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Enhanced Triple Layered Approach for Mitigating Security Risks in Cloud

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computers, Materials & Continua 2025年第4期83卷 719-738页

作者： Tajinder Kumar Purushottam Sharma Xiaochun Cheng Sachin Lalar Shubham Kumar Sandhya Bansal Computer Science&Engineering Department Jai Parkash Mukand Lal Innovative Engineering&Technology InstituteRadaur135133HaryanaIndia School of Computer Science&Engineering Galgotias UniversityGreater Noida203201Uttar PradeshIndia Computer Science Department Bay Campus Fabian WaySwansea UniversitySwanseaSA18ENUK Department of Engineering and Technology Gurugram UniversityGurugram122003India Presidency School of Computer Science Presidency UniversityBangalore560089India Maharishi Markendeshwar Engineering College Maharishi Markandeshwar(Deemed to be)UniversityMullanaAmbala133203India

With cloud computing,large chunks of data can be handled at a small ***,there are some reservations regarding the security and privacy of cloud data *** solving these issues and enhancing cloud computing security,this research provides a Three-Layered Security Access model(TLSA)aligned to an intrusion detection mechanism,access control mechanism,and data encryption *** TLSA underlines the need for the protection of sensitive *** proposed approach starts with Layer 1 data encryption using the Advanced Encryption Standard(AES).For data transfer and storage,this encryption guarantees the data’s authenticity and ***,the solution employs the AES encryption algorithm to secure essential data before storing them in the Cloud to minimize unauthorized ***-based access control(RBAC)implements the second strategic level,which ensures specific personnel access certain data and *** RBAC,each user is allowed a specific role and *** implies that permitted users can access some data stored in the *** layer assists in filtering granular access to data,reducing the risk that undesired data will be discovered during the *** 3 deals with intrusion detection systems(IDS),which detect and quickly deal with malicious actions and intrusion *** proposed TLSA security model of e-commerce includes conventional levels of security,such as encryption and access control,and encloses an insight intrusion detection *** method offers integrated solutions for most typical security issues of cloud computing,including data secrecy,method of access,and *** extensive performance test was carried out to confirm the efficiency of the proposed three-tier security *** have been made with state-of-art techniques,including DES,RSA,and DUAL-RSA,keeping into account Accuracy,QILV,F-Measure,Sensitivity,MSE,PSNR,SSIM,and computation time,encryption time,and decryption *** proposed

关键词： Cloud security:data encryption AES access control intrusion detection systems(IDS) role-based access control(RBAC)

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A Penalty Groups-Assisted Iterated Greedy Integrating Idle Time Insertion:Solving the Hybrid Flow Shop Group Scheduling with Delivery Time Windows

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Complex System Modeling and Simulation 2024年第2期4卷 137-165页

作者： Qianhui Ji Yuyan Han Yuting Wang Biao Zhang Kaizhou Gao the School of Computer Science Liaocheng UniversityLiaocheng 252059China Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China

The hybrid flow shop group scheduling problem(HFGSP)with the delivery time windows has been widely studied owing to its better flexibility and suitability for the current just-in-time production ***,there are several unresolved challenges in problem modeling and algorithmic design tailored for *** our study,we place emphasis on the constraint of ***,this paper first constructs a mixed integer linear programming model of HFGSP with sequence-dependent setup time and delivery time windows to minimize the total weighted earliness and tardiness(TWET).Then a penalty groups-assisted iterated greedy integrating idle time insertion(PG IG ITI)is proposed to solve the above *** the PG IG ITI,a double decoding strategy is proposed based on the earliest available machine rule and the idle time insertion rule to calculate the TWET ***,to reduce the amount of computation,a skip-based destruction and reconstruction strategy is designed,and a penalty groups-assisted local search is proposed to further improve the quality of the solution by disturbing the penalized groups,i.e.,early and tardy ***,through comprehensive statistical experiments on 270 test instances,the results prove that the proposed algorithm is effective compared to four state-of-the-art algorithms.

关键词： hybrid flow shop group scheduling iterated greedy algorithm delivery time windows sequence-dependent setup time

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Leveraging Asynchronous Spiking Neural Networks for Ultra Efficient Event-Based Visual Processing 39

Leveraging Asynchronous Spiking Neural Networks for Ultra Ef...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Zeng, DingYi Wang, Yuchen Cao, Honglin Liu, Wanlong Xiao, Yichen Lu, Chengzhuo Chen, Wenyu Zhang, Malu Wang, Guoqing Yang, Yang School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)157735897X

Event cameras encode visual information by generating asynchronous and sparse event streams, which hold great potential for low latency and low power consumption. Despite many successful implementations of event camera-based applications, most of them accumulate the events into frames and then utilize conventional frame-based computer vision algorithms. These frame-based methods, though typically effective, diminish the inherent advantages of the event camera's low latency and low power consumption. To solve the above problems, we propose ASGCN, which efficiently processes data on an event-by-event basis and dynamically evolves into a corresponding dynamic representation, enabling low latency and high sparsity of data representation. The sparsity computation is further improved by introducing brain-inspired spiking neural networks, resulting in low power consumption for ASGCN. Extensive and diverse experiments demonstrate the energy efficiency and low latency advantages of our processing pipeline. Especially on real-world event camera datasets, our pipeline consumes more than 10,000 times less energy and achieves similar performance compared to current frame-based methods. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

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E2E-LANet: Unleashing the Potential of Linear Attention for High-Resolution Medical Image Segmentation via Pretraining Distillation 24

E2E-LANet: Unleashing the Potential of Linear Attention for ...

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5th International Symposium on Artificial Intelligence for Medicine science, ISAIMS 2024

作者： Tang, Hui Yu, Gang Cao, Lu School of Computer Science and Engineering Hunan University of Science and Technology Hunan Xiangtan China

ISBN: (纸本)9798400717826

Medical image segmentation plays an important role in computer-aid diagnosis. In the past years, convolutional neural networks, especially the UNet-based architectures with symmetric U-shape encoder-decoder structure and skip connection, have been widely used in a variety of medical imaging segmentation tasks. However, such methods are difficult to capture global context. In contrast, Vision Transformers (ViTs) utilize the self-attention mechanism to obtain long-range dependencies in images. Despite these advantages, the huge computational costs of the self-attention mechanism reduce the inference speed of models, thereby limiting their real-world applications. Meanwhile, hierarchical pixel-level decoding of U-shape architectures increases the complexity of large-size segmentation decoding. To address these limitations, in this paper we propose a linear attention-based end-to-end model for high-resolution medical image segmentation, named E2E-LANet. It consists of two modules: an image encoder based on constructed Efficient Vision Transformer (EVT) that reduces the high quadratic complexity of self-attention to linear complexity and a Query-Supported Mask Decoder (QSMD) that employs independent mask query for each type of medical images in segmentation mask predictions. It focuses on the detailed segmentation decoding of patch-level features to further improve the efficiency of large-size mask predictions. Especially, we leverage the advantages of pretraining distillation to improve the transferability of our model in various segmentation tasks. Experimental results on the nucleus segmentation task and the polyp segmentation task display the important role of pretraining distillation in improving the performance of our framework. E2E-LANet demonstrates superior performance compared to CNNs, ViTs, and latest Mamba-based U-shape architectures. © 2024 Copyright held by the owner/author(s).

关键词： Convolutional neural networks

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Parameter Efficient Point Cloud Prompt Tuning for Unified Point Cloud Understanding

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-16页

作者： Fei, Ben Liu, Liwen Yang, Weidong Li, Zhijun Chen, Wen-Ming Ma, Lipeng School of Computer Science Fudan University Shanghai China School of Mechanical Engineering Tongji University Shanghai China Academy for Engineering and Technology Fudan University Shanghai China

The prevailing paradigm in 3D vision involves fully fine-tuning all the backbone parameters of pre-trained models. However, this approach poses challenges due to the large number of parameters requiring tuning, resulting in unexpected storage demands. To address these issues and alleviate the computational cost and storage burden associated with full fine-tuning, we propose Point Cloud Prompt Tuning (PCPT) as an effective method for large Transformer models in point cloud processing. PCPT offers a powerful and efficient solution to mitigate the costs associated with full fine-tuning. Drawing inspiration from recent advancements in efficient tuning of large-scale language models and 2D vision models, PCPT leverages less than 0.05 % of trainable parameters, while keeping the pre-trained parameters of the Transformer backbone unchanged. To evaluate the effectiveness of PCPT, extensive experiments were conducted on four discriminative datasets (ModelNet40, few-shot ModelNet40, ScanObjectNN, ShapeNetPart) and four generation datasets (PCN, MVP, ShapeNet55, and ShapeNet34/Unseen21). The results demonstrate that the task-specific prompts utilized in PCPT enable the Transformer model to adapt effectively to the target domains, yielding results comparable to those obtained through other full fine-tuning methods. This highlights the versatility of PCPT across various domains and tasks. Our code is available at https://***/Fayeben/PCPT. IEEE

关键词： Three dimensional displays

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Facial Action Units as a Joint Dataset Training Bridge for Facial Expression Recognition

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IEEE Transactions on Multimedia 2025年 27卷 3331-3342页

作者： Mao, Shuyi Li, Xinpeng Zhang, Fan Peng, Xiaojiang Yang, Yang Shenzhen Technology University College of Big Data and Internet Guangdong Shenzhen518118 China University of Electronic Science and Technology School of Computer Science and Engineering Sichuan Chengdu611731 China

Label biases in facial expression recognition (FER) datasets, caused by annotators' subjectivity, pose challenges in improving the performance of target datasets when auxiliary labeled data are used. Moreover, training with multiple datasets can lead to visible degradations in the target dataset. To address these issues, we propose a novel framework called the AU-aware Vision Transformer (AU-ViT), which leverages unified action unit (AU) information and discards expression annotations of auxiliary data. AU-ViT integrates an elaborately designed AU branch in the middle part of a master ViT to enhance representation learning during training. Through qualitative and quantitative analyses, we demonstrate that AU-ViT effectively captures expression regions and is robust to real-world occlusions. Additionally, we observe that AU-ViT also yields performance improvements on the target dataset, even without auxiliary data, by utilizing pseudo AU labels. Our AU-ViT achieves performances superior to, or comparable to, that of the state-of-the-art methods on FERPlus, RAFDB, AffectNet, LSD and the other three occlusion test datasets. © 1999-2012 IEEE.

关键词： Labeled data

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Reliability Analysis of Correlated Competitive and Dependent Components Considering Random Isolation Times

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computers, Materials & Continua 2023年第9期76卷 2763-2777页

作者： Shuo Cai Tingyu Luo Fei Yu Pradip Kumar Sharma Weizheng Wang Lairong Yin School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China Department of Computing Science University of AberdeenAberdeenUK School of Automotive and Mechanical Engineering Changsha University of Science and TechnologyChangsha410114China

In the Internet of Things(IoT)system,relay communication is widely used to solve the problem of energy loss in long-distance transmission and improve transmission *** Body Sensor Network(BSN)systems,biosensors communicate with receiving devices through relay nodes to improve their limited energy *** the relay node fails,the biosensor can communicate directly with the receiving device by releasing more transmitting ***,if the remaining battery power of the biosensor is insufficient to enable it to communicate directly with the receiving device,the biosensor will be isolated by the ***,a new combinatorial analysis method is proposed to analyze the influence of random isolation time(RIT)on system reliability,and the competition relationship between biosensor isolation and propagation failure is *** approach inherits the advantages of common combinatorial algorithms and provides a new approach to effectively address the impact of RIT on system reliability in IoT systems,which are affected by competing ***,the method is applied to the BSN system,and the effect of RIT on the system reliability is analyzed in detail.

关键词： BSN Internet of Things reliability analysis random isolation time

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TRS Scheduling for Improved QoS Performance in Cloud System

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computers, Materials & Continua 2023年第4期75卷 1547-1559页

作者： G.John Samuel Babu M.Baskar Department of Computer Science and Engineering School of ComputingCollege of Engineering and TechnologySRM Institute of Science and TechnologyKattankulathurChengalpattuTamilnadu603203India Department of Computing Technologies School of ComputingCollege of Engineering andTechnologySRM Institute of Science and TechnologyKattankulathurChengalpattuTamilnadu603203India

Numerous methods are analysed in detail to improve task schedulingand data security performance in the cloud environment. The methodsinvolve scheduling according to the factors like makespan, waiting time,cost, deadline, and popularity. However, the methods are inappropriate forachieving higher scheduling performance. Regarding data security, existingmethods use various encryption schemes but introduce significant serviceinterruption. This article sketches a practical Real-time Application CentricTRS (Throughput-Resource utilization–Success) Scheduling with Data Security(RATRSDS) model by considering all these issues in task scheduling anddata security. The method identifies the required resource and their claim timeby receiving the service requests. Further, for the list of resources as services,the method computes throughput support (Thrs) according to the number ofstatements executed and the complete statements of the service. Similarly, themethod computes Resource utilization support (Ruts) according to the idletime on any duty cycle and total servicing time. Also, the method computesthe value of Success support (Sus) according to the number of completions forthe number of allocations. The method estimates the TRS score (ThroughputResource utilization Success) for different resources using all these supportmeasures. According to the value of the TRS score, the services are rankedand scheduled. On the other side, based on the requirement of service requests,the method computes Requirement Support (RS). The selection of service isperformed and allocated. Similarly, choosing the route according to the RouteSupport Measure (RSM) enforced route security. Finally, data security hasgets implemented with a service-based encryption technique. The RATRSDSscheme has claimed higher performance in data security and scheduling.

关键词： Cloud task scheduling TRS quality of service RSM route security data security SDE RATRSDS

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