Expert Systems with Applications最新文献_第2页

A multi-task minutiae transformer network for fingerprint recognition of young children

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-02-15 DOI: 10.1016/j.eswa.2025.126825

Manhua Liu , Aitong Liu , Yelin Shi , Shuxin Liu

{"title":"A multi-task minutiae transformer network for fingerprint recognition of young children","authors":"Manhua Liu , Aitong Liu , Yelin Shi , Shuxin Liu","doi":"10.1016/j.eswa.2025.126825","DOIUrl":"10.1016/j.eswa.2025.126825","url":null,"abstract":"<div><div>Fingerprint recognition of children have attracted increasing attention for real applications such as identity certificate. However, the recognition performance is greatly reduced if the existing systems are directly used on the fingerprints of young children due to their low resolution and poor image quality. Towards more accurate fingerprint recognition of young children, this paper proposes multi-task deep learning framework based on Pyramid Densely-connected U-shaped Swin-transformer network (PDUSwin-Net) to jointly learn the reconstruction of enhanced high-resolution images and detection of minutiae points, which is compatible with existing adult fingerprint sensors (500 dpi) and minutiae matchers. First, a pyramid densely-connected U-shaped convolutional network is proposed to learn the features of fingerprints for multiple tasks. Then, a swin-transformer attention block is added to model the correlations of long-spatial features. In the decoding part, two branches are built for the tasks of fingerprint enhancement and minutiae extraction. Finally, our method is tested with the existing matchers on two independent fingerprint datasets of young children aged from 0–2 years. Results and comparison show that our method performs better than other methods for fingerprint recognition of young children.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"273 ","pages":"Article 126825"},"PeriodicalIF":7.5,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Stockformer: A price–volume factor stock selection model based on wavelet transform and multi-task self-attention networks

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-02-15 DOI: 10.1016/j.eswa.2025.126803

Bohan Ma , Yushan Xue , Yuan Lu, Jing Chen

{"title":"Stockformer: A price–volume factor stock selection model based on wavelet transform and multi-task self-attention networks","authors":"Bohan Ma , Yushan Xue , Yuan Lu, Jing Chen","doi":"10.1016/j.eswa.2025.126803","DOIUrl":"10.1016/j.eswa.2025.126803","url":null,"abstract":"<div><div>As the Chinese stock market continues to evolve and its market structure grows increasingly complex, traditional quantitative trading methods face escalating challenges. Due to policy uncertainty and frequent market fluctuations triggered by sudden economic events, existing models often struggle to predict market dynamics accurately. To address these challenges, this paper introduces “Stockformer,” a price–volume factor stock selection model that integrates wavelet transformation and a multitask self-attention network to enhance responsiveness and predictive accuracy regarding market instabilities. Through discrete wavelet transform, Stockformer decomposes stock returns into high and low frequencies, meticulously capturing long-term market trends and short-term fluctuations, including abrupt events. Moreover, the model incorporates a Dual-Frequency Spatiotemporal Encoder and graph embedding techniques to capture complex temporal and spatial relationships among stocks effectively. Employing a multitask learning strategy, it simultaneously predicts stock returns and directional trends. Experimental results show that Stockformer outperforms existing advanced methods on multiple real stock market datasets. In strategy backtesting, Stockformer consistently demonstrates exceptional stability and reliability across market conditions—whether rising, falling, or fluctuating—particularly maintaining high performance during downturns or volatile periods, indicating high adaptability to market fluctuations. To foster innovation and collaboration in the financial analysis sector, the Stockformer model’s code has been open-sourced and is available on the GitHub repository: <span><span>https://github.com/Eric991005/Multitask-Stockformer</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"273 ","pages":"Article 126803"},"PeriodicalIF":7.5,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic programming-based exact and heuristic algorithms for single machine scheduling with sequence-dependent setups

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-02-15 DOI: 10.1016/j.eswa.2025.126866

Tengmu Hu , Shih-Hsien Tseng , Theodore T. Allen

{"title":"Dynamic programming-based exact and heuristic algorithms for single machine scheduling with sequence-dependent setups","authors":"Tengmu Hu , Shih-Hsien Tseng , Theodore T. Allen","doi":"10.1016/j.eswa.2025.126866","DOIUrl":"10.1016/j.eswa.2025.126866","url":null,"abstract":"<div><div>This study presents a novel algorithmic framework and an inventory flow mixed integer programming formulation designed to minimize total tardiness and the number of setups. The approach decomposes the problem into three stages: intra-family scheduling, family sequence optimization, and family-switch timing. We propose a specialized heuristic with <span><math><mrow><mi>O</mi><mrow><mo>(</mo><msup><mrow><mi>n</mi></mrow><mrow><mn>5</mn></mrow></msup><mo>log</mo><mi>n</mi><mo>)</mo></mrow></mrow></math></span> complexity efficiently handles intra-family scheduling and is extended to accommodate subfamily groupings. Dynamic programming is employed for family-switch optimization, with state complexity constrained to <span><math><mrow><msup><mrow><mn>2</mn></mrow><mrow><mi>n</mi></mrow></msup><mo>+</mo><mn>1</mn></mrow></math></span>. In the last stage of algorithmic framework, we propose a branch-and-bound method to handle family-switch timing, utilizing lower bounds derived from the results of previous stages. Our overall proposed ”branch-and-bound-regulated dynamic programming (B&B-DP)” algorithm excels in solving large-scale scheduling problems, demonstrating superior performance against four benchmark methods across 150 test cases. This algorithmic framework extends the capabilities of single-machine scheduling with family setup times to handle a large number of jobs. In our experiments, we show that the proposed algorithm reduces total tardiness by 10%–25% compared to other methods. This research not only advances the state of the art in single-machine scheduling but also provides a scalable and effective framework for addressing complex production scheduling challenges.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"273 ","pages":"Article 126866"},"PeriodicalIF":7.5,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143438082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Maximizing data utility while preserving privacy through database fragmentation

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-02-15 DOI: 10.1016/j.eswa.2025.126873

Ali Amiri

{"title":"Maximizing data utility while preserving privacy through database fragmentation","authors":"Ali Amiri","doi":"10.1016/j.eswa.2025.126873","DOIUrl":"10.1016/j.eswa.2025.126873","url":null,"abstract":"<div><div>Efficiently managing databases that balance data privacy with utility is a critical challenge in today’s data-driven landscape. This study addresses the problem of database fragmentation, which involves dividing a database into smaller fragments, each containing a subset of attributes. The primary objective is to strike a balance between safeguarding the confidentiality of sensitive attribute sets and optimizing the database’s utility. Sensitive attribute sets include combinations of attributes that could disclose private information or identify individuals, such as personal quasi-identifiers, necessitating their separation into distinct fragments to reduce the risk of sensitive data exposure. Conversely, utility attribute sets consist of attributes that enhance data usability and query efficiency. Maximizing utility requires grouping attributes from the same utility set into as few fragments as possible. To effectively solve this complex NP-hard problem, A column generation-based solution leveraging a set partitioning formulation is presented. Experimental evaluations on real and synthetic datasets validate the efficiency of the proposed approach, demonstrating its superiority over the state-of-the-art commercial solver, CPLEX.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"273 ","pages":"Article 126873"},"PeriodicalIF":7.5,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143438160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development and validation of a human-machine interface for unmanned aerial vehicle (UAV) control via hand gesture teleoperation

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-02-15 DOI: 10.1016/j.eswa.2025.126828

Fevzi Çakmak Bolat , Mustafa Cem Avci

{"title":"Development and validation of a human-machine interface for unmanned aerial vehicle (UAV) control via hand gesture teleoperation","authors":"Fevzi Çakmak Bolat , Mustafa Cem Avci","doi":"10.1016/j.eswa.2025.126828","DOIUrl":"10.1016/j.eswa.2025.126828","url":null,"abstract":"<div><div>In this research, a drone-style unmanned aerial vehicle is maneuvered using hand gestures through the creation of a specialized glove design. The analytical formulas pertaining to the drone framework developed during the research were derived, leading to the establishment of a mathematical representation. These formulas were implemented in the Matlab & Simulink environment, and simulations of the system based on this mathematical representation were conducted. Next, to carry out verification tests, a unique device was crafted and set up for the drone, enabling real-time data exchange with the glove. A series of distinct signal sets for the glove were examined to confirm the functionality of the system. After confirming the control mechanism, it was seamlessly incorporated into the electronic hardware framework, leveraging the Arduino Uno microcontroller as the focal point. Within the hand gesture apparatus, an innovative circuit was devised, managed by the Atmega328P microcontroller chip. The primary motivation behind this exploration resides in the desire to establish a user interface for UAV operators that is both seamless and unobtrusive, moving beyond the artificial and cumbersome elements tied to traditional control systems. For this purpose, the research aims to empower users to utilize hand gestures—frequently employed in various everyday scenarios—for piloting activities, thus improving user performance and simplicity of use. The findings of this study highlight the parity between the glove apparatus designed for hand gesture manipulation and the conventional joystick-based system, thereby confirming its effectiveness for multiple applications. Furthermore, a one-handed method was embraced for hand gesture control, with the supplementary aim of offering pilot training opportunities for individuals with upper limb impairments.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"273 ","pages":"Article 126828"},"PeriodicalIF":7.5,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Beyond-Skeleton: Zero-shot Skeleton Action Recognition enhanced by supplementary RGB visual information

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-02-15 DOI: 10.1016/j.eswa.2025.126814

Hongjie Liu , Yingchun Niu , Kun Zeng , Chun Liu , Mengjie Hu , Qing Song

{"title":"Beyond-Skeleton: Zero-shot Skeleton Action Recognition enhanced by supplementary RGB visual information","authors":"Hongjie Liu , Yingchun Niu , Kun Zeng , Chun Liu , Mengjie Hu , Qing Song","doi":"10.1016/j.eswa.2025.126814","DOIUrl":"10.1016/j.eswa.2025.126814","url":null,"abstract":"<div><div>Zero-shot action recognition (ZSAR) recognizes action categories that have not appeared during the training process and has garnered widespread attention due to its potential to save costs in retraining and data annotation. We observed that the existing ZSAR method based on skeleton sequences only uses human posture information in the skeleton sequence, lacks discriminative semantic representation in some similar behavior recognition, and lacks effective interaction between different modalities, resulting in unsatisfactory performance and limited applications of the ZSAR. To solve these problems, we propose a novel method, called Beyond-Skeleton zero-shot Learning (BSZSL), which is used to enhance zero-shot Skeleton Action Recognition. Firstly, a multi-prompt learning strategy is introduced. It utilizes prompt information to guide the model to simultaneously learn complementary semantic information related to behavior categories from both skeleton sequences and RGB information, making the visual feature information more expressive. Specifically, it employs a pre-trained multimodal model to extract prior knowledge related to behaviors from RGB and then guides the skeleton sequence features using this knowledge. This enhances the complementary features of both RGB and skeleton modalities. Secondly, to constrain the mapping relationship of different modal feature information, a Contrastive Clustering (CC) module is designed. This module emphasizes the similarity of features within the same category while increasing the differences in feature mapping between different categories. Finally, evaluating our method on the NTU-60 and NTU-120 datasets with multi-split settings, the result demonstrates that our method achieves state-of-the-art performance in both zero-shot learning (ZSL) and generalized zero-shot learning (GZSL) settings.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"273 ","pages":"Article 126814"},"PeriodicalIF":7.5,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ODTE—An ensemble of multi-class SVM-based oblique decision trees

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-02-15 DOI: 10.1016/j.eswa.2025.126833

Ricardo Montañana, José A. Gámez, José M. Puerta

{"title":"ODTE—An ensemble of multi-class SVM-based oblique decision trees","authors":"Ricardo Montañana, José A. Gámez, José M. Puerta","doi":"10.1016/j.eswa.2025.126833","DOIUrl":"10.1016/j.eswa.2025.126833","url":null,"abstract":"<div><div>We propose ODTE, a new ensemble that uses oblique decision trees as base classifiers. Additionally, we introduce STree, the base algorithm for growing oblique decision trees, which leverages support vector machines to define hyperplanes within the decision nodes. We embed a multiclass strategy (one-vs-one or one-vs-rest) at the decision nodes, allowing the model to directly handle non-binary classification tasks without the need to cluster instances into two groups, as is common in other approaches from the literature. In each decision node, only the best-performing model (SVM)—the one that minimizes an impurity measure for the n-ary classification—is retained, even if the learned SVM addresses a binary classification subtask. An extensive experimental study involving 49 datasets and various state-of-the-art algorithms for oblique decision tree ensembles has been conducted. Our results show that ODTE ranks consistently above its competitors, achieving significant performance gains when hyperparameters are carefully tuned. Moreover, the oblique decision trees learned through STree are more compact than those produced by other algorithms evaluated in our experiments.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"273 ","pages":"Article 126833"},"PeriodicalIF":7.5,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Joint optimization of quality control and maintenance policy for a production system with quality-dependent failures

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-02-14 DOI: 10.1016/j.eswa.2025.126800

Jingjing Wang , Lingyun Luo , Guoqing Mu , Yingying Ma , Chao Ni

{"title":"Joint optimization of quality control and maintenance policy for a production system with quality-dependent failures","authors":"Jingjing Wang , Lingyun Luo , Guoqing Mu , Yingying Ma , Chao Ni","doi":"10.1016/j.eswa.2025.126800","DOIUrl":"10.1016/j.eswa.2025.126800","url":null,"abstract":"<div><div>A machine is either subject to hard failure or soft failure, while quality-dependent failure is usually ignored in production systems. However, in practice, non-conforming products generally accelerate the degradation process of production systems. To fill these gaps, this paper formulated an integrated model of the optimal quality control policy and maintenance policies under the quality-dependent failures for production systems. Since the severe degradation of product machines directly impacts the non-conforming rate, effective preventive and opportunistic maintenance actions are necessary. Moreover, the production system can timely be corrected from an out-of-control state to a control state after adopting a minimal repair. An opportunity is created based on the buffer inventory level instead of the machine degradation level, which is different from previous research. The production machine can be opportunistically maintained at the point of maximum inventory. The renewal process is utilized to derive the integrated optimization model, and the collaboration relationship among production, quality control and maintenance management problems is taken into consideration. The system’s total cost rate is minimized by optimizing the preventive maintenance threshold and sampling control coefficients. Numerical examples are given to illustrate the priority of the proposed model and the optimal results are obtained by differential evaluation algorithm, which provides a more meaningful perspective for managers.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"272 ","pages":"Article 126800"},"PeriodicalIF":7.5,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Graph Attention Networks For Anomalous Drone Detection: RSSI-Based Approach with Real-world Validation

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-02-14 DOI: 10.1016/j.eswa.2025.126913

Ghulam E Mustafa Abro , Ayman M Abdallah

{"title":"Graph Attention Networks For Anomalous Drone Detection: RSSI-Based Approach with Real-world Validation","authors":"Ghulam E Mustafa Abro , Ayman M Abdallah","doi":"10.1016/j.eswa.2025.126913","DOIUrl":"10.1016/j.eswa.2025.126913","url":null,"abstract":"<div><div>The swift proliferation of unmanned aerial vehicles (UAVs) and their expanding applications have engendered considerable security apprehensions, especially with the detection of anomalous drones inside swarms. This research introduces an innovative methodology utilising Graph Attention Networks (GAT) and Received Signal Strength Indicator (RSSI) data to discover and identify abnormal drones in UAV networks. The suggested method employs a V-cycle algorithm-based graph attention model, wherein RSSI deviations from the mean are calculated for each drone node and utilised as a feature within the graph. A radius graph is created to illustrate drone-to-drone conversations, facilitating the computation of attention scores that assess the significance of each node’s connectivity and RSSI attributes. Drones displaying irregular RSSI patterns, as detected by the GAT framework, are identified as potential dangers or anomalous drones. The system is engineered to manage intricate real-world settings by effectively detecting drones exhibiting aberrant behaviour via multilevel graph coarsening and refinement methodologies. To assess the efficacy of the suggested strategy, simulations were executed, and empirical experiments were carried out with the Robolink Codrones kit. The trials validated the system’s capability to identify drones exhibiting anomalous signal strength fluctuations in real-time situations. The findings illustrate the suggested method’s efficacy in detecting anomalous drones using RSSI anomalies, surpassing conventional detection techniques in accuracy and computing efficiency. RSSI data and graph attention approaches for autonomous drone identification can improve UAV network security and anomaly detection systems, as shown in this study.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"273 ","pages":"Article 126913"},"PeriodicalIF":7.5,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143438163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Inspired by “Focus, Fusion, Collaboration”: A multi-level ensemble network for automatic pneumonia diagnosis from full slice CT images

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-02-14 DOI: 10.1016/j.eswa.2025.126806

Linna Zhao, Jianqiang Li, Qing Zhao, Xi Xu

{"title":"Inspired by “Focus, Fusion, Collaboration”: A multi-level ensemble network for automatic pneumonia diagnosis from full slice CT images","authors":"Linna Zhao, Jianqiang Li, Qing Zhao, Xi Xu","doi":"10.1016/j.eswa.2025.126806","DOIUrl":"10.1016/j.eswa.2025.126806","url":null,"abstract":"<div><div>Pneumonia is an infectious disease that endangers human health. With advancements in science and technology, deep learning-driven techniques have gained prominence in this field. However, their applicability to clinical practice remains limited because they mostly neglect three key points: focus on local lesion regions, multi-level feature fusion, and sequential collaborative decision-making. In this paper, we present a novel multi-level ensemble network for automatic pneumonia diagnosis from full slice CT images, inspired by the “Focus, Fusion, Collaboration” strategy. Our proposed model involves three modules: the global–local feature extraction module is first designed to fully extract the global structure information and local lesion details; subsequently, the multi-level feature fusion module is responsible for integrating the above-mentioned global and local information; finally, the sequential pneumonia prediction module is utilized to learn the contextual relationship between the adjacent slices, thus generating the final diagnosis results. Building upon mimicking the diagnostic behavior from real-world clinical scenarios, our model enables the integration of multiple types of information (including global structure information, local lesion features, and slice dependencies) and sequential pneumonia diagnosis. Extensive comparative experiments are conducted to verify the feasibility and effectiveness of our proposed method. The experimental results show that our model can obtain an accuracy of 91.4% in a four-class pneumonia diagnosis task, outperforming the other classical works.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"273 ","pages":"Article 126806"},"PeriodicalIF":7.5,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0