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Automated recognition of hypertension through overnight continuous HRV monitoring

JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED computing 2018年第6期9卷 2011-2023页

作者： Ni, Hongbo Cho, Sunyoung Mankoff, Jennifer Yang, Jun Dey, Anind k. Northwestern Polytech Univ Sch Comp Sci Xian Shaanxi Peoples R China Carnegie Mellon Univ Pittsburgh PA 15213 USA Beijing Aviat Med Inst Beijing Peoples R China

Hypertension is a common and chronic disease, caused by high blood pressure. Since hypertension often has no warning signs or symptoms, many cases remain undiagnosed. Untreated or sub-optimally controlled hypertension may lead to cardiovascular, cerebrovascular and renal morbidity and mortality, along with dysfunction of the autonomic nervous system. Therefore, it could be quite valuable to predict or provide early warnings about hypertension. Heart rate variability (HRV) analysis has emerged as the most valuable non-invasive test to assess autonomic nervous system function, and has great potential for detecting hypertension. However, HRV indicators may be subtle and present at random, resulting in two challenges: how to support continuous monitoring for hours at a time while being unobtrusive, and how to efficiently analyze the collected data to minimize data collection and user burden. In this paper, we present a machine learning-based approach for detecting hypertension, using a waist belt continuous sensing system that is worn overnight. Using 24 hypertension patients and 24 healthy controls, we demonstrate that our approach can differentiate hypertension patients from healthy controls with 93.33% accuracy. This represents a promising approach for performing hypertension classification in the field, and also we would improve its performance based on a large number of hypertensive subjects monitored by the proposed pervasive sensors.

关键词： Human-centered computing Ubiquitous computing computing methodologies Machine learning Electrocardiogram Pyramid methods Healthcare Heart rate sensing

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Efficient Decoding of Affective States from Video-elicited EEG Signals: An Empirical Investigation

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ACM TRANSACTIONS ON MULTIMEDIA computing COMMUNICATIONS AND APPLICATIONS 2024年第10期20卷 1-24页

作者： Latifzadeh, Kayhan Gozalpour, Nima Traver, V. Javier Ruotsalo, Tuukka Kawala-Sterniuk, Aleksandra Leiva, Luis A. Univ Luxembourg Esch Sur Alzette Luxembourg Univ Jaume 1 INIT Castellon de la Plana Spain Univ Copenhagen Copenhagen Denmark LUT Univ Lahti Finland Opole Univ Technol Opole Poland

Affect decoding through brain-computer interfacing (BCI) holds great potential to capture users' feelings and emotional responses via non-invasive electroencephalogram (EEG) sensing. Yet, little research has been conducted to understand efficient decoding when users are exposed to dynamic audiovisual contents. In this regard, we study EEG-based affect decoding from videos in arousal and valence classification tasks, considering the impact of signal length, window size for feature extraction, and frequency bands. We train both classic Machine Learning models (SVMs and k-NNs) and modern Deep Learning models (FCNNs and GTNs). Our results show that: (1) affect can be effectively decoded using less than 1 minute of EEG signal;(2) temporal windows of 6 and 10 seconds provide the best classification performance for classic Machine Learning models but Deep Learning models benefit from much shorter windows of 2 seconds;and (3) any model trained on the Beta band alone achieves similar (sometimes better) performance than when trained on all frequency bands. Taken together, our results indicate that affect decoding can work in more realistic conditions than currently assumed, thus becoming a viable technology for creating better interfaces and user models.

关键词： Human-centered computing User models Ambient intelligence computing methodologies Machine learning approaches

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Structure-Information-Based Reasoning over the Knowledge Graph: A Survey of Methods and Applications

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ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA 2024年第8期18卷 1-42页

作者： Meng, Siyuan Zhou, Jie Chen, Xuxin Liu, Yufei Lu, Fengyuan Huang, Xinli East China Normal Univ Shanghai 200062 Peoples R China

The knowledge graph (KG) is an efficient form of knowledge organization and expression, providing prior knowledge support for various downstream tasks, and has received extensive attention in natural language processing. However, existing large-scale KGs have many hidden facts that need to be discovered. How to effectively use the structure information of KG is an important research direction of knowledge reasoning. Structure-Information-based reasoning over the KG is a technique used to find the missing facts by the structure information of KG. This survey summarizes the methods and applications of Structure-Information- based reasoning and hopes to be helpful to the research in this field. First, we introduced the definition of knowledge reasoning and the conceptual description of related tasks. Then, we reviewed the methods of Structure-Information-based reasoning. Specifically, we categorized them into four representative classes: PRA-based reasoning, Path-Embedding-based reasoning, RL-based reasoning, and GNN-based reasoning. We compared the motivations and details between practices in the same category. After that, we described the application of Structure-Information-based knowledge reasoning in the KG Completion, Question Answering System, Recommendation System, and other fields. Finally, we discussed the future research directions of Structure-Information-based reasoning.

关键词： General and reference Surveys and overviews computing methodologies Knowledge representation and reasoning

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Purchasing Power: Rivalry, Dissent, and computing Strategy in Supercomputer Selection at Los Alamos

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IEEE ANNALS OF THE HISTORY OF computing 2017年第3期39卷 25-40页

作者： Lewis, Nicholas Univ Minnesota Hist Sci Technol & Med Program Minneapolis MN 55455 USA

In the Mid-1960s, the Laboratory at Los Alamos, New Mexico, a center of scientific computing since the Manhattan Project, embarked on a search for a new supercomputer intended to fulfill the growing need for computing power in nuclear weapons development. Although depicted at Los Alamos in later years as a smooth transition between vendors, the selection process was a contentious negotiation among computing experts and users over their differing visions of computing and its place at Los Alamos. This article argues that changing technical and political demands on weapons design and Los Alamos's place in the rivalry between IBM and Control Data Corporation further complicated the selection process and challenged the traditional control and direction of Los Alamos's computing strategy. The result was the formation of a new computing division and a reframing of the debate over the long-standing management and purpose of computing at Los Alamos.

关键词： and visualization application services and standards case studies in government case studies in scientific applications cold war Computational modeling computer system implementation computing methodologies control data corporation Feature extraction ibm large and medium (“mainframe”) computers los alamos modeling Nuclear weapons Process control Scientific computing services computing simulation super (very large) computers Supercomputers

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Persistent inter-observer variability of breast density assessment using BI-RADS® 5th edition guidelines

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CLINICAL IMAGING 2022年第0期83卷 21-27页

作者： Portnow, Leah H. Georgian-Smith, Dianne Haider, Irfanullah Barrios, Mirelys Bay, Camden P. Nelson, Kerrie P. Raza, Sughra Brigham & Womens Hosp Dept Radiol 75 Francis St Boston MA 02115 USA Boston Univ Dept Biostat 801 Massachusetts Ave3rd Floor Boston MA 02118 USA

Objectives: Due to most states' legislation, mammographic density categorization has potentially far-reaching implications, but remains subjective based on BIRADS (R) guidelines. We aimed to determine 1) effect of BI-RADS (R) 5th edition (5th-ed) vs 4th-edition (4th-ed) guidelines on reader agreement regarding density assessment;2) 5th-ed vs 4th-ed density distribution, and visual vs quantitative assessment agreement;3) agreement between experienced vs less experienced readers. Methods: In a retrospective review, six breast imaging radiologists (BIR) (23-30 years' experience) visually assessed density of 200 screening mammograms performed September 2012-January 2013 using 5th-ed guidelines. Results were compared to 2016 data of the same readers evaluating the same mammograms using 4th-ed guidelines after a training module. 5th-ed density categorization by seven junior BIR (1-5 years' experience) was compared to eight experienced BIR. Nelson et al.'s kappas (kappa(m) , kappa(w)), Fleiss' kappa(F), and Cohen's kappa were calculated. Quantitative density using Volpara was compared with reader assessments. Results: Inter-reader weighted agreement using 5th-ed is moderately strong, 0.73 (kappa(w), s.e. = 0.01), similar to 4th-ed, 0.71 (kappa(w), s.e. = 0.03). Intra-reader Cohen's kappa is 0.23-0.34, similar to 4th-ed. Binary not-dense vs dense categorization, using 5th-ed results in higher dense categorization vs 4th-ed (p < 0.001). 5th-ed density distribution results in higher numbers in categories B/C vs 4th-ed (p < 0.001). Distribution for 5th-ed does not differ based on reader experience (p = 0.09). Reader vs quantitative weighted agreement is similar (5th-ed, Cohen's kappa = 0.76-0.85;4th-ed, Cohen's kappa = 0.68-0.83). Conclusion: There is persistent subjectivity of visually assessed mammographic density using 5th-ed guidelines;experience does not correlate with better inter-reader agreement.

关键词： Breast density Mammography computing methodologies Algorithms

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Personality and emotion-based high-level control of affective story characters

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2007年第2期13卷 281-293页

作者： Su, Wen-Poh Pham, Binh Wardhani, Aster Queensland Univ Technol Fac Informat Technol Brisbane Qld 4001 Australia

Human emotional behavior, personality, and body language are the essential elements in the recognition of a believable synthetic story character. This paper presents an approach using story scripts and action descriptions in a form similar to the content description of storyboards to predict specific personality and emotional states. By adopting the Abridged Big Five Circumplex (AB5C) Model of personality from the study of psychology as a basis for a computational model, we construct a hierarchical fuzzy rule-based system to facilitate the personality and emotion control of the body language of a dynamic story character. The story character can consistently perform specific postures and gestures based on his/her personality type. Story designers can devise a story context in the form of our story interface which predictably motivates personality and emotion values to drive the appropriate movements of the story characters. Our system takes advantage of relevant knowledge described by psychologists and researchers of storytelling, nonverbal communication, and human movement. Our ultimate goal is to facilitate the high-level control of a synthetic character.

关键词： computing methodologies simulation modelling visualization types of simulation animation computer applications social and behavioral sciences psychology

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The HIDENETS Holistic Approach for the Analysis of Large Critical Mobile Systems

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IEEE TRANSACTIONS ON MOBILE computing 2011年第6期10卷 783-796页

作者： Bondavalli, Andrea Hamouda, Ossama Kaaniche, Mohamed Lollini, Paolo Majzik, Istvan Schwefel, Hans-Peter Univ Florence Dipartimento Sistemi & Informat I-50134 Florence Italy Univ Toulouse LAAS CNRS UPS INSAINPISAELAAS F-31077 Toulouse France Budapest Univ Technol & Econ Dept Measurement & Informat Syst H-1117 Budapest Hungary Forschungszentrum Telekommunikat Wien FTW GmbH A-1220 Vienna Austria Aalborg Univ Inst Elect Syst DK-9220 Aalborg Denmark

Dealing with large, critical mobile systems and infrastructures where ongoing changes and resilience are paramount leads to very complex and difficult challenges for system evaluation. These challenges call for approaches that are able to integrate several evaluation methods for the quantitative assessment of QoS indicators which have been applied so far only to a limited extent. In this paper, we propose the holistic evaluation framework developed during the recently concluded FP6-HIDENETS project. It is based on abstraction and decomposition, and it exploits the interactions among different evaluation techniques including analytical, simulative, and experimental measurement approaches, to manage system complexity. The feasibility of the holistic approach for the analysis of a complete end-to-end scenario is first illustrated presenting two examples where mobility simulation is used in combination with stochastic analytical modeling, and then through the development and implementation of an evaluation workflow integrating several tools and model transformation steps.

关键词： Computer systems organization communication/networking and information technology mobile computing mobile communication systems computing methodologies simulation modeling and visualization model development modeling methodologies computer applications mobile applications pervasive computing

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The Phosphorylation of the Heat Shock Factor as a Modulator for the Heat Shock Response

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2012年第5期9卷 1326-1337页

作者： Czeizler, Eugen Rogojin, Vladimir Petre, Ion Aalto Univ Sch Sci Dept Informat & Comp Sci FI-00076 Aalto Finland Helsinki Inst Informat Technol Helsinki Finland Univ Helsinki Biomedicum Helsinki Fac Med FIN-00014 Helsinki Finland Abo Akad Univ Dept Informat Technol FIN-20520 Turku Finland

The heat shock response is a well-conserved defence mechanism against the accumulation of misfolded proteins due to prolonged elevated heat. The cell responds to heat shock by raising the levels of heat shock proteins (hsp), which are responsible for chaperoning protein refolding. The synthesis of hsp is highly regulated at the transcription level by specific heat shock (transcription) factors (hsf). One of the regulation mechanisms is the phosphorylation of hsf's. Experimental evidence shows a connection between the hyper-phosphorylation of hsfs and the transactivation of the hsp-encoding genes. In this paper, we incorporate several (de) phosphorylation pathways into an existing well-validated computational model of the heat shock response. We analyze the quantitative control of each of these pathways over the entire process. For each of these pathways we create detailed computational models which we subject to parameter estimation in order to fit them to existing experimental data. In particular, we find conclusive evidence supporting only one of the analyzed pathways. Also, we corroborate our results with a set of computational models of a more reduced size.

关键词： Simulation modeling computing methodologies biology and genetics computer applications heat shock response protein phosphorylation quantitative refinement

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Semantic Classification of Byzantine Icons

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IEEE INTELLIGENT SYSTEMS 2009年第2期24卷 35-43页

作者： Tzouveli, Paraskevi Simou, Nikos Stamou, Giorgios Kollias, Stefanos Natl Tech Univ Athens Dept Elect & Comp Engn GR-10682 Athens Greece Natl Tech Univ Athens Sch Elect & Comp Engn GR-10682 Athens Greece

The painters of Byzantine and post-Byzantine icons use specific rules and iconographic patterns. On the basis of these rules and patterns, a proposed knowledge-based image analysis system classifies icons. First, the system detects and analyzes the most important facial characteristics, providing rich, yet still imprecise, information about the icon. Then, it expresses the extracted information in terms of an expressive terminology formalized using a description logic (DL). To effectively handle the imprecision, the system uses a fuzzy extension of a DL to produce assertional knowledge. The combination of the terminological and assertional knowledge allows the system to categorize the icons. Tests of the system on a repository of 2,000 Byzantine icons has produced promising results.

关键词： Knowledge Representation Formalisms And Methods Artificial Intelligence Scene Analysis Image Processing Computer Vision Design Methodology Pattern Recognition computing methodologies

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Provenance in agent-mediated healthcare systems

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IEEE INTELLIGENT SYSTEMS 2006年第6期21卷 38-46页

作者： Kifor, Tamas Varga, Laszlo Z. Vazquez-Salceda, Javier Alvarez, Sergio Willmott, Steven Miles, Simon Moreau, Luc Comp & Automat Res Inst H-1111 Budapest Hungary Univ Politecn Cataluna Dept Llenguatges & Sist Informat E-08034 Barcelona Spain Univ Southampton Southampton SO9 5NH Hants England

This article is part of a special issue on Intelligent Agents in Healthcare. Healthcare information systems can use agent-oriented cooperation techniques and standardized, electronic healthcare-record-exchange protocols to combine information about the different facets of a patient's therapy provided by different healthcare providers at different locations. Provenance is an innovative approach to tracing events in complex distributed processes. It also traces dependencies between such events and associated decisions by human actors. This article focuses on three aspects of provenance in agent-mediated healthcare systems. First, it defines provenance and shows how to apply it in agent-mediated healthcare applications. Second, it introduces a method that lets independent, autonomous healthcare agents that don't directly interact document their processes. Third, it shows how this approach helps institutions contend with privacy issues.

关键词： Internet applications artificial intelligence computer applications computing methodologies data dependencies database management distributed artificial intelligence healthcare information technology and systems information technology and systems applica data dependency Health Care Systems network technology system network applications Intelligent agents Health Personnel Health Care computing methodologies Artificial Intelligence APPLIED COMPUTER SCIENCE patient treatment Distributed Artificial Intelligence database management

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