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A Game Platform for Treatment of Amblyopia

IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING 2011年第3期19卷 280-289页

作者： To, Long Thompson, Benjamin Blum, Jeffrey R. Maehara, Goro Hess, Robert F. Cooperstock, Jeremy R. McGill Univ Ctr Intelligent Machines Montreal PQ H3A 2A7 Canada Univ Auckland Dept Optometry & Vis Sci Auckland 1071 New Zealand McGill Univ Dept Ophthalmol Montreal PQ H3A 2A7 Canada

We have developed a prototype device for take-home use that can be used in the treatment of amblyopia. The therapeutic scenario we envision involves patients first visiting a clinic, where their vision parameters are assessed and suitable parameters are determined for therapy. Patients then proceed with the actual therapeutic treatment on their own, using our device, which consists of an Apple iPod Touch running a specially modified game application. Our rationale for choosing to develop the prototype around a game stems from multiple requirements that such an application satisfies. First, system operation must be sufficiently straightforward that ease-of-use is not an obstacle. Second, the application itself should be compelling and motivate use more so than a traditional therapeutic task if it is to be used regularly outside of the clinic. This is particularly relevant for children, as compliance is a major issue for current treatments of childhood amblyopia. However, despite the traditional opinion that treatment of amblyopia is only effective in children, our initial results add to the growing body of evidence that improvements in visual function can be achieved in adults with amblyopia.

关键词： Biology biomedical engineering brain stimulation cognition cognitive informatics cybernetics medical diagnosis medical treatment neural engineering physiology psychology psychometric testing sensitivity and specificity

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Power Series Representation Model of Text Knowledge Based on Human Concept Learning

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2014年第1期44卷 86-102页

作者： Luo, Xiangfeng Zhang, Jun Ye, Feiyue Wang, Peng Cai, Chuanliang Shanghai Univ High Performance Comp Ctr Sch Comp Engn & Sci Shanghai 200444 Peoples R China Jiangnan Inst Comp Technol Wuxi 214083 Peoples R China

How to build a text knowledge representation model, which carries rich knowledge and has a flexible reasoning ability as well as can be automatically constructed with a low computational complexity, is a fundamental challenge for reasoning-based knowledge services, especially with the rapid growth of web resources. However, current text knowledge representation models either lose much knowledge [e. g., vector space model (VSM)] or have a high complex computation [e. g., latent Dirichlet allocation (LDA)];even some of them cannot be constructed automatically [e. g., web ontology language, (OWL)]. In this paper, a novel text knowledge representation model, power series representation (PSR) model, which has a low complex computation in text knowledge constructing process, is proposed to leverage the contradiction between carrying rich knowledge and automatic construction. First, concept algebra of human concept learning is developed to represent text knowledge as the form of power series. Then, degree-2 power series hypothesis is introduced to simplify the proposed PSR model, which can be automatically constructed with a lower complex computation and has more knowledge than the VSM and LDA. After that, degree-2 power series hypothesis-based reasoning operations are developed, which provide a more flexible reasoning ability than OWL and LDA. Furthermore, experiments and comparisons with current knowledge representation models show that our model has better characteristics than others when representing text knowledge. Finally, a demo is given to indicate that PSR model has a good prospect over the area of web semantic search.

关键词： cognitive informatics human concept learning knowledge representation semantic search text understanding

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A layered reference model of the brain (LRMB)

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IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS 2006年第2期36卷 124-133页

作者： Wang, Y Wang, Y Patel, S Patel, D Univ Calgary Theoret & Empir Software Engn Res Ctr Calgary AB T2N 1N4 Canada Fourth City Hosp Xian 710004 Shaanxi Peoples R China S Bank Univ Sch Comp Informat Syst & Math London SE1 0AA England

A variety of life functions and cognitive processes (CPs) have been identified in cognitive informatics, psychology, cognitive science, and neurophilosophy. This paper attempts to develop a layered reference model of the brain (LRMB) that formally and rigorously explains the functional mechanisms and CPs of natural intelligence. A comprehensive and coherent set of mental processes and their relationships is identified in LRMB that encompasses 37 CPs at six layers known as the sensation, memory, perception, action, metacognitive, and higher cognitive layers from the bottom-up. The LRMB reference model provides an integrated framework for modeling the brain and the mind. LRMB also enables future extension and refinement of the CPs within the same hierarchical framework. LRMB can be applied to explain a wide range of physiological, psychological, and cognitive phenomena in cognitive informatics, particularly the relationships and interactions between the inherited and the acquired life functions, as well as those of the subconscious and conscious CPs.

关键词： autonomic computing cognitive informatics cognitive processes (CPs) natural intelligence (NI) neuropsychology reference model the brain

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ON CONCEPT ALGEBRA FOR COMPUTING WITH WORDS (CWW)

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INTERNATIONAL JOURNAL OF SEMANTIC COMPUTING 2010年第3期4卷 331-356页

作者： Wang, Yingxu Univ Calgary Dept Elect & Comp Engn 2500 Univ Dr NW Calgary AB T2N 1N4 Canada

Computing with words (CWW) is an intelligent computing methodology for processing words, linguistic variables, and their semantics, which mimics the natural-language-based reasoning mechanisms of human beings in soft computing, semantic computing, and cognitive computing. The central objects in CWW techniques are words and linguistic variables, which may be formally modeled by abstract concepts that are a basic cognitive unit to identify and model a concrete entity in the real world and an abstract object in the perceived world. Therefore, concepts are the most fundamental linguistic entities that carries certain meanings in expression, thinking, reasoning, and system modeling, which may be formally modeled as an abstract and dynamic mathematical structure in denotational mathematics. This paper presents a formal theory for concept and knowledge manipulations in CWW known as concept algebra. The mathematical models of abstract and concrete concepts are developed based on the object-attributerelation (OAR) theory. The formal methodology for manipulating knowledge as a concept network is described. Case studies demonstrate that concept algebra provides a generic and formal knowledge manipulation means, which is capable of dealing with complex knowledge and their algebraic operations in CWW.

关键词： Computing with word concept algebra semantic computing denotational mathematics cognitive informatics concept network knowledge representation OAR model soft computing cognitive computing computational intelligence case studies

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Accuracy is in the eyes of the pathologist: The visual interpretive process and diagnostic accuracy with digital whole slide images

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JOURNAL OF BIOMEDICAL informatics 2017年 66卷 171-179页

作者： Brunye, Tad T. Mercan, Ezgi Weaver, Donald L. Elmore, Joann G. Tufts Univ Ctr Appl Brain & Cognit Sci 200 Boston AveSuite 3000 Medford MA 02155 USA Univ Washington Dept Comp Sci & Engn Seattle WA 98195 USA Univ Vermont Dept Pathol Burlington VT 05405 USA Univ Vermont UVM Canc Ctr Burlington VT USA Univ Washington Sch Med Dept Med Seattle WA 98195 USA

Digital whole slide imaging is an increasingly common medium in pathology, with application to education, telemedicine, and rendering second opinions. It has also made it possible to use eye tracking devices to explore the dynamic visual inspection and interpretation of histopathological features of tissue while pathologists review cases. Using whole slide images, the present study examined how a pathologist's diagnosis is influenced by fixed case-level factors, their prior clinical experience, and their patterns of visual inspection. Participating pathologists interpreted one of two test sets, each containing 12 digital whole slide images of breast biopsy specimens. Cases represented four diagnostic categories as determined via expert consensus: benign without atypia, atypia, ductal carcinoma in situ (DCIS), and invasive cancer. Each case included one or more regions of interest (ROIs) previously determined as of critical diagnostic importance. During pathologist interpretation we tracked eye movements, viewer tool behavior (zooming, panning), and interpretation time. Models were built using logistic and linear regression with generalized estimating equations, testing whether variables at the level of the pathologists, cases, and visual interpretive behavior would independently and/or interactively predict diagnostic accuracy and efficiency. Diagnostic accuracy varied as a function of case consensus diagnosis, replicating earlier research. As would be expected, benign cases tended to elicit false positives, and atypia, DCIS, and invasive cases tended to elicit false negatives. Pathologist experience levels, case consensus diagnosis, case difficulty, eye fixation durations, and the extent to which pathologists' eyes fixated within versus outside of diagnostic ROIs, all independently or interactively predicted diagnostic accuracy. Higher zooming behavior predicted a tendency to over-interpret benign and atypia cases, but not DCIS cases. Efficiency was not predicted b

关键词： Pathology Breast cancer Decision making Whole slide imaging cognitive informatics

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Autonomous Agents and Ethical Decision-Making

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cognitive COMPUTATION 2016年第2期8卷 278-296页

作者： Cervantes, Jose-Antonio Rodriguez, Luis-Felipe Lopez, Sonia Ramos, Felix Robles, Francisco CINVESTAV Dept Comp Sci Guadalajara Jalisco Mexico Inst Tecnol Sonora Dept Comp Sci Hermosillo Sonora Mexico Univ Guadalajara North Ctr Dept Well Being & Sustainable Dev Guadalajara 44430 Jalisco Mexico

Machine ethics, also known as artificial morality, is a newly emerging field concerned with ensuring appropriate behavior of machines toward humans and other machines. In this article, we discuss the importance of machine ethics and present a computational model of ethical decision-making for autonomous agents. The proposed model implements a mechanism for integrating the results of diverse assessments into a unique cue, and takes into account the agent's preferences, good and bad past experiences, ethical rules, and current emotional state as the main factors involved in choosing the most appropriate option. The design of the model is based on theories and models developed in fields such as neuroscience, psychology, artificial intelligence, and cognitive informatics. In particular, the model attempts to emulate neural mechanisms of the human brain involved in ethical decision-making.

关键词： Ethical decision-making Artificial moral agent Machine ethics cognitive informatics cognitive process

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Recovery at the edge of error: Debunking the myth of the infallible expert

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JOURNAL OF BIOMEDICAL informatics 2011年第3期44卷 413-424页

作者： Patel, Vimla L. Cohen, Trevor Murarka, Tripti Olsen, Joanne Kagita, Srujana Myneni, Sahiti Buchman, Timothy Ghaemmaghami, Vafa Univ Texas Hlth Sci Ctr Sch Biomed Informat Ctr Cognit Informat & Decis Making UTHlth Houston Houston TX 77030 USA Arizona State Univ Dept Biomed Informat Tempe AZ 85287 USA Emory Univ Sch Med Dept Surg Atlanta GA USA Banner Good Samaritan Med Ctr Phoenix AZ USA

The notion that human error should not be tolerated is prevalent in both the public and personal perception of the performance of clinicians. However, researchers in other safety-critical domains have long since abandoned the quest for zero defects as an impractical goal, choosing to focus instead on the development of strategies to enhance the ability to recover from error. This paper presents a cognitive framework for the study of error recovery, and the results of our empirical research into error detection and recovery in the critical care domain, using both laboratory-based and naturalistic approaches. Both attending physicians and residents were prone to commit, detect and recover from errors, but the nature of these errors was different. Experts corrected the errors as soon as they detected them and were better able to detect errors requiring integration of multiple elements in the case. Residents were more cautious in making decisions showing a slower error recovery pattern, and the detected errors were more procedural in nature with specific patient outcomes. Error detection and correction are shown to be dependent on expertise, and on the nature of the everyday tasks of the clinicians concerned. Understanding the limits and failures of human decision-making is important if we are to build robust decision-support systems to manage the boundaries of risk of error in decision-making. Detection and correction of potential error is an integral part of cognitive work in the complex, critical care workplace. (C) 2010 Elsevier Inc. All rights reserved.

关键词： Error detection Error recovery cognitive informatics Naturalistic Laboratory-based Patient safety Decision making Expertise

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Measuring Algebraic Complexity of Text Understanding Based on Human Concept Learning

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IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS 2014年第5期44卷 638-649页

作者： Luo, Xiangfeng Zhang, Jun Li, Qing Wei, Xiao Lu, Lei Shanghai Univ Sch Comp Engn & Sci Shanghai 200444 Peoples R China City Univ Hong Kong Kowloon Hong Kong Peoples R China City Univ Hong Kong Multimedia Software Engn Res Ctr Dept Comp Sci Kowloon Hong Kong Peoples R China

This paper advocates for a novel approach to recommend texts at various levels of difficulties based on a proposed method, the algebraic complexity of texts (ACT). Different from traditional complexity measures that mainly focus on surface features like the numbers of syllables per word, characters per word, or words per sentence, ACT draws from the perspective of human concept learning, which can reflect the complex semantic relations inside texts. To cope with the high cost of measuring ACT, the Degree-2 Hypothesis of ACT is proposed to reduce the measurement from unrestricted dimensions to three dimensions. Based on the principle of "mental anchor," an extension of ACT and its general edition [denoted as extension of text algebraic complexity (EACT) and general extension of text algebraic complexity (GEACT)] are developed, which take keywords' and association rules' complexities into account. Finally, using the scores given by humans as a benchmark, we compare our proposed methods with linguistic models. The experimental results show the order GEACT>EACT>ACT> Linguistic models, which means GEACT performs the best, while linguistic models perform the worst. Additionally, GEACT with lower convex functions has the best ability in measuring the algebraic complexities of text understanding. It may also indicate that the human complexity curve tends to be a curve like lower convex function rather than linear functions.

关键词： cognitive informatics text understanding web search

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The Use of Data Mining Methods for the Prediction of Dementia: Evidence From the English Longitudinal Study of Aging

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IEEE JOURNAL OF BIOMEDICAL AND HEALTH informatics 2020年第2期24卷 345-353页

作者： Yang, Hui Bath, Peter A. Univ Sheffield Informat Sch Sheffield S1 4DP S Yorkshire England

Dementia in older age is a major health concern with the increase in the aging population. Preventive measures to prevent or delay dementia symptoms are of utmost importance. In this study, a large and wide variety of factors from multiple domains were investigated using a large nationally representative sample of older people from the English Longitudinal Study of Ageing. Seven machine learning algorithms were implemented to build predictive models for performance comparison. A simple model ensemble approach was used to combine the prediction results of individual base models to further improve predictive power. A series of important factors in each domain area were identified. The findings from this study provide new evidence on factors that are associated with the dementia in later life. This information will help our understanding of potential risk factors for dementia and identify warning signs of the early stages of dementia. Longitudinal research is required to establish which factors may be causative and which factors may be a consequence of dementia.

关键词： Mental health cognitive informatics gerontechnology

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Efficient and Robust Pupil Size and Blink Estimation from Near-Field Video Sequences for Human-Machine Interaction

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IEEE TRANSACTIONS ON CYBERNETICS 2014年第12期44卷 2356-2367页

作者： Chen, Siyuan Epps, Julien Univ New S Wales Sch Elect Engn & Telecommun Sydney NSW 2052 Australia Natl ICT Australia ATP Res Lab Sydney NSW 2015 Australia

Monitoring pupil and blink dynamics has applications in cognitive load measurement during human-machine interaction. However, accurate, efficient, and robust pupil size and blink estimation pose significant challenges to the efficacy of real-time applications due to the variability of eye images, hence to date, require manual intervention for fine tuning of parameters. In this paper, a novel self-tuning threshold method, which is applicable to any infrared-illuminated eye images without a tuning parameter, is proposed for segmenting the pupil from the background images recorded by a low cost webcam placed near the eye. A convex hull and a dual-ellipse fitting method are also proposed to select pupil boundary points and to detect the eyelid occlusion state. Experimental results on a realistic video dataset show that the measurement accuracy using the proposed methods is higher than that of widely used manually tuned parameter methods or fixed parameter methods. Importantly, it demonstrates convenience and robustness for an accurate and fast estimate of eye activity in the presence of variations due to different users, task types, load, and environments. cognitive load measurement in human-machine interaction can benefit from this computationally efficient implementation without requiring a threshold calibration beforehand. Thus, one can envisage a mini IR camera embedded in a lightweight glasses frame, like Google Glass, for convenient applications of real-time adaptive aiding and task management in the future.

关键词： Biometrics cognitive informatics human factors image segmentation pervasive computing

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