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Titlebook: Bioengineering and Biomedical Signal and Image Processing; First International Ignacio Rojas,Daniel Castillo-Secilla,Héctor Pomar Conferen

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發(fā)表于 2025-3-21 17:10:53 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱(chēng)Bioengineering and Biomedical Signal and Image Processing
期刊簡(jiǎn)稱(chēng)First International
影響因子2023Ignacio Rojas,Daniel Castillo-Secilla,Héctor Pomar
視頻videohttp://file.papertrans.cn/187/186922/186922.mp4
學(xué)科分類(lèi)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Bioengineering and Biomedical Signal and Image Processing; First International  Ignacio Rojas,Daniel Castillo-Secilla,Héctor Pomar Conferen
影響因子This book constitutes the refereed proceedings of the First International Conference on Bioengineering and Biomedical Signal and Image Processing., .BIOMESIP 2021, held in Meloneras, Gran Canaria, Spain, in July 2021.. The 41 full and 5 short papers were carefully reviewed and selected from 121 submissions. The papers are grouped in topical issues on biomedical applications in molecular, structural, and functional imaging; biomedical computing; biomedical signal measurement, acquisition and processing; computerized medical imaging and graphics; disease control and diagnosis; neuroimaging; pattern recognition and machine learning for biosignal data; personalized medicine; and COVID-19.. .
Pindex Conference proceedings 2021
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書(shū)目名稱(chēng)Bioengineering and Biomedical Signal and Image Processing影響因子(影響力)




書(shū)目名稱(chēng)Bioengineering and Biomedical Signal and Image Processing影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Bioengineering and Biomedical Signal and Image Processing網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Bioengineering and Biomedical Signal and Image Processing網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Bioengineering and Biomedical Signal and Image Processing被引頻次




書(shū)目名稱(chēng)Bioengineering and Biomedical Signal and Image Processing被引頻次學(xué)科排名




書(shū)目名稱(chēng)Bioengineering and Biomedical Signal and Image Processing年度引用




書(shū)目名稱(chēng)Bioengineering and Biomedical Signal and Image Processing年度引用學(xué)科排名




書(shū)目名稱(chēng)Bioengineering and Biomedical Signal and Image Processing讀者反饋




書(shū)目名稱(chēng)Bioengineering and Biomedical Signal and Image Processing讀者反饋學(xué)科排名




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Automatic Classification of Valve Diseases Through Natural Language Processing in Spanish and Activech limits its use and quality. We propose a proof of concept based on Natural Language Processing and active learning, in order to automatically structure information from a text in Spanish in the field of echocardiography..Echocardiographic reports from a Health National System Cardiology Departmen
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Focal and Generalized Seizures Distinction by Rebalancing Class Data and Random Forest Classificatioileptic seizures differ depending on their origin in the brain. They can be categorized as either focal or generalized in onset. The identification of seizure category is essential in brain surgery and in selecting medications that could help bring seizures under control. It is not always feasible t
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Event Related Potential Analysis Using Machine Learning to Predict Diagnostic Outcome of Autism Specent Related Potentials (ERPs) have identified abnormal patterns of brain activity in high-risk infants who go onto ASD diagnosis. In this study, we used well-established ERP components related to face processing. Features of these ERPs were used to explore the performance of machine learning algorit
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Natural Cellulosic Fiber Reinforced Bio-Epoxy Based Composites and Their Mechanical Propertiesderived from epoxy is used as matrix. Four different types of fibers e.g., jute, sisal, coconut/coir and sugarcane (bagasse) were used for reinforcement. Fibers were used with three different loading levels by volume i.e., 20%, 25% and 30% respectively. Mechanical properties e.g., impact strength, f
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Modelling Brain Connectivity Networks by Graph Embedding for Dyslexia Diagnosistype of Cross-Frequency Coupling (CFC) method, consisting in measure the synchronization of phase and amplitude for the different EEG bands and electrodes. This provides information regarding brain areas that are synchronously activated, and eventually, a marker of functional connectivity between th
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Causal Coupling of Low Frequency Oscillations During Movement Imagination – A Multimodal Studyency range during movement imagination. The relationships between the signals were found using Directed Transfer Function based on the Granger causality principle. The study yielded a comprehensive scheme of reciprocal interactions, which was compared with the scheme obtained for the real movement.
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