Computer Science calls for papers / publications

Call for Papers for a Special Issue of the International Journal of Nano and Biomaterials: Machine Learning and Pattern Recognition in Bioinformatics

Guest Editors:
Prof. Feng Liu and Prof. Wen Zhang, Wuhan University, China

Currently, a great amount of data are being generated which range from gene expression and micro RNA array data through to next generation sequence data. Data interpretation draws on mathematical and computational skills and thus the subject has engaged the interest of researchers in areas such mathematics, bioinformatics and computer science.

This cross-disciplinary special issue aims to bring together top researchers, practitioners and students from all over the world to explore and present innovative machine learning and pattern recognition approaches to solve realistic problems in bioinformatics and biomedicine.

Subject Coverage

Suitable topics include but are not limited to:

Microarray gene expression data analysis
Protein structure and function prediction
Molecular interaction and regulation network inference
Immunoinformatics and cheminformatics
High throughput sequencing data analysis
Text mining in biomedical literatures
Algorithms in molecular modelling
Biological databases, integration and visualisation
New machine learning methods for bioinformatics
Genome-wide association studies
Biomarker discovery
Gene network analysis
Tools and algorithms in bioinformatics
Other related topics  

Notes for Prospective Authors

Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper was not originally copyrighted and if it has been completely re-written).

All papers are refereed through a peer review process. A guide for authors, sample copies and other relevant information for submitting papers are available on the Author Guidelines page http://www.inderscience.com/mapper.php?id=31

Important Dates

Full paper deadline: 25 July, 2012

Acceptance notification: 15 September, 2012

Final revised submission: 10 October, 2012

All papers must be submitted online.

Call for Papers for a Special Issue of Cognitive Technology Journal: Designing Educational Games

The use of computer games as common vehicles for impacting cognition, as opposed to pure entertainment, has recently gained immense popularity. Games may be developed to educate children about their health condition or to improve their understanding of math or history, examine economic policies, encourage the discussion of public health policy for individuals, or to encourage change in user's lifestyle. The proliferation of games has profound implications not only for the entertainment industry, but also for the research community interested in studying the impact of using such games on cognitive abilities of the users.

In this Special Issue, Cognitive Technology will bring together researchers from across the world to consider new research that illustrates the potential of computer games as a cognitive technology for teaching and learning. Guest editors, Dr. Nilufar Baghaei and Dr. Aaron Chen, are seeking original research papers that illustrate the capacity or potential of games for enhancing the users' learning experience and increasing their knowledge of any domain ranging from health-related issues to math and languages.

Topics of Interest

The international journal of Cognitive Technology is planning a special issue on designing educational games (expected publication Spring 2013). Authors are invited to submit papers describing original research (applied or theoretical), that deal with innovative approaches of using game technologies as cognitive tools for increasing the learning outcome of the users and/or enhancing their learning experience.

We invite papers that address one of the following topics, or a closely related one:

Educational games as a cognitive technology for learning

Designing educational games for people with disabilities and/or health conditions

Integrating games with health care applications

Intelligent Tutoring Systems and adaptive educational games

Designing, developing and evaluating educational games on mobile devices

Understanding the problems and limitations of using games as cognitive technologies

Best practices for designing educational games based on cognitive science

Empirical or case studies of increasing users' motivation for learning using educational games

Empirical studies of educational games and their effectiveness in increasing users' domain knowledge

Empirical or case studies of perceptual and cognitive advantages and disadvantages of educational games

Future directions of designing, developing and deploying educational games in instructional settings

Submission and Format

Research papers submitted for this journal should be original and must not exceed 15 double-spaced manuscript pages inclusive of title page, abstract page, references, figures, tables, and appendices. The papers should be submitted to Dr. Baghaei or Dr. Chen via email. They should be prepared in line with the formatting guidelines of Cognitive Technology Journal. Additional details about final manuscript format requirements will be sent upon notification of acceptance.

For queries regarding the special issue, the guest editors can be contacted at: nbaghaei@unitec.ac.nz or achen2@unitec.ac.nz
Important Dates

August 24, 2012: Paper submission deadline
September 28, 2012: Peer reviews completed
October 26, 2012: Re-submission of revised papers
November 23, 2012: Submission of camera ready versions
Spring 2013: Journal publication

Guest Editors

Dr. Nilufar Baghaei, Dept of Computing, UNITEC, New Zealand
Dr. Aaron Chen, Dept of Computing, UNITEC, New Zealand
Dr. Paul Pivec, CranberryBlue R&D (UK/NZ) Ltd, New Zealand

Call for Papers for a Special Issue of the Journal of Web Semantics: Data Linking

This special issue of the Journal of Web Semantics focuses on the problem of finding links between datasets published as linked data.

Today the web of data has become a reality. The ever increasing number of datasets published as RDF according to the linked data principles, the support of major search engines, e-commerce sites and social networks give no doubt that the early scenarios of the semantic Web vision will soon become a reality.

The power of the web lies in its networked structure, in the connections between the resources it contains. Similarly, linked data enable the interlinking of data resources so that databases become interconnected and the information they contain become part of a huge distributed database. The transformation of the Web from a “Web of documents” into a “Web of data”, as well as the availability of large collections of sensor generated data (“internet of things”), is leading to a new generation of Web applications based on the integration of both data and services. At the same time, new data are published every day out of user generated contents and public Web sites.

This emergence of the Web of data raises many challenges, such as the need of comparing and matching data with the goal of resolving the multiplicity of data references to the same real-world objects and of finding useful and relevant similarities and correspondences among data. The Web needs techniques and tools for the discovery of data links, and a suitable theory for the understanding and definition of the data links meaning.

About data links, one of the most important goals is to provide means to ensure that the interconnection between data is effective. The design of algorithms, methodologies, languages and tools that provide more efficient and automated ways to link data is essential for the growth of the Web of data rather than a set of disjoint data islands.

While the problems of entity resolution have been studied in the database community for a long time, the Web of data environment presents new important challenges at different levels. Large volumes of data and the variety of repositories which have to be processed rise the need for scalable linking techniques which require minimal user involvement. On the other hand, in cases where user configuration effort is required, there is a need for tools to be usable by non-experts in the domain.

Given that published data links can be used by automatic reasoning tools, it is important to capture the meaning of links in a precise way. Since quality of automatically generated links can vary, their provenance and reliability have to be modelled in an explicit way. Finally, to capture and compare the reliability of different tools and techniques, there is a need for evaluation methods for automatic data linking approaches.

Challenges

• Automating the process of finding links between Web datasets
• Scaling data linking algorithms
• Representation and interpretation of links
• Providing efficient user interfaces and interaction methods
• Modeling and reasoning on links trust and provenance information

Topics of Interest

The topics of interest for this special issue include but are not limited to the following.

• data linking tools and frameworks
• techniques for automated data linking
• data similarity measures
• similarity spreading measures
• schema-based similarity measures
• candidate dataset selection and datasets similarity measures
• statistical analysis techniques
• semi-supervised, learning-based data linking methods
• optimization methods for computing similarity
• web data sampling techniques
• identity representation and semantics
• reasoning on links, link propagation
• user interaction for link elicitation and validation
• provenance and trust models on links
• methods for link quality assessment
• innovative applications using links
• evaluation of data linking techniques and tools

Important Dates

We will review papers on a rolling basis as they are submitted and explicitly encourage submissions well before the final deadline.

• 1 June: submission deadline
• 1 September: initial decisions and notifications
• 1 October: major/minor revisions due
• 1 November: final minor revisions due
• 1 December: final decisions and notifications
• 1 January: preprints available publication in 2013

Instructions for submission

Please see the author guidelines for detailed instructions before you submit. Submissions should be conducted through Elsevier’s Electronic Submission System. More details on the Journal of Web Semantics can be found on its homepage. See the JWS Guide for Authors for details on the submission process.

Editors

• Alfio Ferrara (Università degli Studi di Milano)
• Andriy Nikolov (Open University)
• François Scharffe (LIRMM, Université de Montpellier 2)

Call for Papers for a Special Issue of the Semantic Web Journal: Big Data and the Semantic Web

The Semantic Web journal calls for innovative and high-quality papers describing the role of Semantic Web technologies, Linked Data, and ontologies for the Big Data age. Papers should clearly relate to one or more of the Big Data V's Volume, Variety, and Velocity, as well as demonstrate the added value of semantics. Besides theoretical contributions on reasoning over massive amounts of heterogeneous data and challenges for knowledge representation and interlinkage, we especially also invite reports from domain scientists detailing the use of ontologies and Semantic Web technologies in bioinformatics, geographic information science, life sciences, cultural heritage research, the digital humanities, and other research areas.

We welcome all paper categories, i.e., full research papers, application reports, systems and tools, ontology papers, surveys, as well as dataset reports as long as they clearly relate to challenges and opportunities arising from processing Big Data - see our listing of paper types in the author guidelines http://www.semantic-web-journal.net/authors

Topics include but are not limited to

Semantic search and information seeking
Exploratory interfaces for massive amounts of annotated data
Intelligent information interchange
Semantic interoperability and heterogeneity
Inductive and abductive approaches to ontology learning
Handling uncertainty, vagueness, and inconsistencies
Knowledge discovery from linked data
Collaborative Ontology engineering
Microtheories and knowledge patterns
Ontology modularization
Ontology evolution
Ontology alignment, matching, and translation
Analogy and similarity reasoning and retrieval
Sensor semantics and smart dust
Stream reasoning
Distributed reasoning
Semantics-based data aggregation and generalization
Semantically enabled statistics
Massive data integration for the digital earth
Linked science
The User as knowledge engineer
Semantics and decision support systems
Semantics-driven integrity constraint checking
Mining the Social and Mobile Web
Ontology-driven data visualization
Trust and privacy issues in publishing and reasoning about Big Data
Dialog and question answering systems based on Linked Data and ontologies

Important Dates
Manuscript submission due: 30th of June 2012
First notification: 7th of September 2012
Issue publication: Spring 2013

Submissions
The special issue on Big Data and the Semantic Web calls for original high-quality research on any of the above mentioned topics. Authors are requested to follow the author guidelines, submit online as detailed in the author guidelines, and include the name of the call within the submission letter. All manuscripts will be reviewed based on the SWJ open and transparent review policy and will be made available during online the review process.

Call for Papers for a Special Issue of the International Journal of Ad Hoc and Ubiquitous Computing: BikeNet: Theory, Technology and Application

Guest Editors:
Prof. Kun Ming Yu and Prof. James Chang Wu Yu, Chung Hua University, Taiwan
Dr. Lei Shu, Osaka University, Japan

BikeNet is a mobile sensing system for cyclists which uses a number of sensors embedded into a cyclist’s bicycle to collect quantitative data about the cyclist’s rides. Researchers need to design practical distributed and centralised algorithms and to introduce novel theoretical models or evaluation methodologies to address various kinds of research problems originating from BikeNet.

Although there are a large number of developed network protocols for wireless sensor networks and ad hoc networks, the unique characteristics of BikeNet – such as limited bandwidth capacity, small size and high mobility – lead to considerable challenges in their design.

The special issue is intended to disseminate high-quality research in BikeNet, and to push theoretical and practical research forward for a deeper understanding of the fundamental algorithms, modelling, and analysis techniques for BikeNet. Authors are invited to submit papers presenting new research related to the theory or practice of BikeNet, including algorithms, modelling, technology and application. All submissions must describe original research, and must not be published or currently under review for another workshop, conference or journal.

The issue will carry revised and substantially extended versions of selected papers presented at the Workshop on Performance Evaluation of Wireless Networks (PEWiN-2012; http://people.chu.edu.tw/~pewin/2012)), but we also strongly encourage researchers unable to participate in the workshop to submit papers for this call.

Subject Coverage

Suitable topics include but are not limited to:

Algorithms, theory and applications for BikeNet, including mobile ad hoc networks, wireless sensor networks, and any kind of multi-hop wireless networks used in BikeNet
Theoretical graph and geometric models for BikeNet
Complexity analysis of algorithms for BikeNet environments
Routing algorithms and strategies in BikeNet
Power optimisation strategies in BikeNet
Throughput, capacity, and delay analysis in BikeNet
Data and resource management in BikeNet
Clustering and cooperative strategies in BikeNet
Coverage and survivability problems in BikeNet
Information theory and network coding for BikeNet
Security, privacy and cryptographic protocols theory for BikeNet

Notes for Prospective Authors

Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper was not originally copyrighted and if it has been completely re-written).

All papers are refereed through a peer review process. A guide for authors, sample copies and other relevant information for submitting papers are available on the Author Guidelines page.

Important Dates
Deadline for submission: 31 October, 2012

Acceptance notification (1st round): 31 April, 2013

Revision submission: 31 June, 2013

Final notification of acceptance: 31 August, 2013

Editors and Notes

All papers must be submitted online. If you experience any problems submitting your paper online, please contact submissions@inderscience.com, describing the exact problem you experience. (Please include in your email the title of the Special Issue, the title of the Journal and the names of the Guest Editors).

Please contact Prof. James Chang Wu Yu (cwyu@chu.edu.tw), Prof. Kun Ming Yu (yu@chu.edu.tw) or Dr. Lei Shu (lei.shu@ist.osaka-u.ac.jp) with any queries concerning this special issue.

Call for Papers for a Special Issue of Artificial Intelligence in Medicine:Evaluation of Clinical Decision Support Systems (CDSS) in Health Care

Guest Editors:
Elske Ammenwerth, UMIT, Hall in Tirol, Austria
Nicolette de Keizer, University of Amsterdam, Dept Medical Informatics, The Netherlands
Michael Rigby, Keele University, U.K.
Pirkko Nykänen, Tampere University

Clinical Decision Support Systems (CDSS) in Health Care have a long history going back to the 1970s, with recent reviews showing that their number and uptake increases. CDSS can support many different activities such as diagnosis, therapy, monitoring or prevention and are used in all kinds of medical domains such as chronic illness, acute care, primary care, and patient advice lines. CDSS may provide many different services such as access to knowledge, statistical calculations and individual adaptations, recommendations, reminders or alerts to different user groups including physicians and nurses but also addressing self-management by patients. In some areas, CDSS have been found to increase clinical performance and guidelines adherence, while evidence on improvement of patient outcome is still limited. There are even examples of negative impact. Overall, the number of published CDSS evaluation studies is still limited given their` rising uptake, and the evaluation design and/or reporting of the evaluation studies is often weak, which makes judgment of their cost-benefit ratio difficult.

The momentum surrounding CDSS is even more increasing with the more widespread implementation of electronic patient records enabling CDSS implementation; however health care providers and organizations and development agencies require more intensive evaluation and research for better informed investments, to ensure patient safety, and to recognize clinician anxieties as to their professional liability. Evidence from early CDSS deployments should be informing and guiding subsequent projects to ensure that ineffective approaches are not duplicated and early successes can be replicated and scaled. Building up such an evidence base requires reproducible and well designed evaluation studies of CDSS. Guidelines for evaluation of health informatics interventions in general and their reporting are available although these need to be adapted and extended for the specific case of CDSS evaluation. Also the updated EU Medical Device Directive now defines "medical” software a medical device. This has implications for the way CDSS are developed and evaluated. Safety for patients, users and others is a key aspect of the evaluation of CDSS in the context of the Medical Device Directive.

As with any aspect of healthcare, policies and practice should be firmly based on evidence, and informatics should be no exception. Evaluation of systems is a robust source of such evidence, provided the evaluation is scientific. Whilst generic guidelines now exist for health informatics systems evaluation, application within CDSS is limited, not least because of the methodological issues arising, especially for pilot studies preceding wider general roll-out. In particular, user populations may be dispersed and hard to reach, user profiles and patterns of use are important factors and patient (and organizational) outcomes are hard to track. This special issue will give opportunity to focus on these challenges.

Topics for the special issue
We are inviting people from health care, academia and industry to submit original articles or systematic reviews relevant to the following topics:

Case studies on evaluation of CDSS
Meta analyses or systematic reviews on CDSS
Methodology of CDSS evaluation
Verification, Validiation and testing of CDSS
Impact of CDSS
Costs of CDSS
CDSS and patient safety
Barriers and challenges to CDSS implementation and evaluation
User acceptance and usability of CDSS
Adoption of CDSS in health care environments
Issue of "brittleness” of CDSS
Quality indicators for CDSS
Certification of CDSS
Future of CDSS evaluation

Deadline of submissions:
Deadline for the submission of manuscripts is June 30th, 2012.

We advise all authors interested to contribute to this special issue to contact Elske Ammenwerth beforehand (contact data see below) to indicate the topic of the planned manuscript.

Instruction for authors:
Please consult the Guide for Authors of AIIM available at the journal homepage at: http://ees.elsevier.com/aiim/

The length of manuscripts should not exceed 20 – 25 manuscript pages (1.5-spaced lines).

When submitting the paper, please use the Electronic Manuscript Submission at http://ees.elsevier.com/aiim/

Clearly indicate that it is a submission to the special issue by adding "Special Issue: CDSS Evaluation” to the title of the manuscript.

All papers are refereed through an international peer review process by at least three reviewers.

Artificial Intelligence in Medicine carries no page charges.

The corresponding author, at no cost, will be provided with a PDF file of the article via e-mail or, alternatively, 25 free paper offprints. See instructions for authors for details.

Contact:
Univ.-Prof. Dr. Elske Ammenwerth
Eduard Wallnöfer Zentrum 1
UMIT – University for Health Sciences, Medical Informatics and Technology
Institute of Medical Informatics
6060 Hall in Tyrol
Austria
Mail elske.ammenwerth@umit.athttp://iig.umit.at

Call for Papers for a Special Issue of Future Generation Computer Systems: Extreme Scale Parallel Architectures and Systems

This special issue invites submissions from researchers working on Experimental Infrastructures for Exascale Research and Development. Work in this area includes investigation of experimental components and systems for extreme-scale, simulation methods and tools targeting extreme scale, benchmarking, application characterisation workload generation tools, and other related experimental systems and methods.

Submissions are encouraged on disruptive approaches to address the challenges of research and development for systems that do not exist as-of-yet. Another aspect of equal importance is the creation of a palette of scientific methods and experimental infrastructures (in software and/or hardware) to evaluate novel ideas (technologies, algorithms, systems). Some of the pressing issues that need to be addressed in this context are scalability of experiments, validation/extrapolation of scientific results, and characterization of expected workloads and their synthetic generation. Given the high cost of ownership and the limited access to the top-end of parallel systems, it is important to pursue experimental architectures and systems comprising of off-the-shelf components, configured, modified, or enhanced in such a way that they can provide insight into aspects of exascale systems.

Topics

Topics of interest include, but are not limited to:

Testbed design and evaluation
Experimental clusters/systems targeting extreme scale
Workload generation and benchmarking
Exascale application characterisation
Analytical modelling and simulation of systems
Techniques for extrapolation of experimental results to extreme-scale
Validation of projection/extrapolation techniques
Suitability/adaptability of commercial, off-the-shelf components (COTS)
Cost, energy, performance and resilience
Methodologies and tools
Co-design approaches

Important Dates

Full paper submission deadline: 29 June 2012
Review results and notification of acceptance: 31 August 2012
Final revised paper: 31 October 2012
Publication: February 2013

Guest Editors

Shoukat Ali, Exascale Systems, IBM Research, Ireland (ALISHOU8@ie.ibm.com)
Kostas Katrinis, Exascale Systems, IBM Research, Ireland (katrinisk@ie.ibm.com)
Rolf Riesen, Exascale Systems, IBM Research, Ireland (rolf.riesen@ie.ibm.com)
Georgios Theodoropoulos, Exascale Systems, IBM Research, Ireland (geortheo@ie.ibm.com)

Submission Format

Submissions must be written in English. Papers must contain novel ideas and must differ significantly in content from previously published papers and papers under simultaneous submission. Authors should prepare and submit manuscripts according to the Guide for Authors in the following link: http://www.elsevier.com/wps/find/journaldescription.cws_home/505611/authorinstructions

If you have any questions about paper submission or the special issue, please contact one of the Guest Editors.

Call for Papers for a Special Issue of Artificial Intelligence in Medicine: Medical Data Streams

An Elsevier Journal

Many artificial intelligence researchers coming from different areas (data mining, machine learning, intelligent data analysis, pattern recognition, fuzzy logic, databases, etc.) design new approaches or adapt some of the traditional algorithms to data streams. In many medical applications different domain experts, e.g. physicians (would) benefit from the integration of the streaming medical data into decision support systems.

The goal of this special issue is to gather researchers who deal with artificial intelligence for data processing, data management and knowledge discovery in clinical scenarios where data is produced as a continuous stream.

IMPORTANT DATES

Submission deadline: 18 Jun 2012 *
Review notification: 18 Sept 2012
Revised submission: 18 Nov 2012
Second notification: 18 Dec 2012
Camera-ready submission: 18 Jan 2013

* earlier submissions are welcome; review process will start immediately after submission

RATIONALE

Artificial Intelligence in Medicine is facing a new challenge, created by the rapid growth in information science and technology in general and the complexity and volume of data in particular. Medical settings are using sensors and networks of health information systems to integrate data from patients, which requires storage, processing and management operators to enable further analysis and knowledge discovery. The main issue is that this data production often takes the form of high-speed continuous flows of data.

Medical domains include several settings where data is produced in a streaming fashion, such as anatomical and physiological sensors, or incidence records and health information systems. New services appear allowing users to store and track information about their medical history, to connect to and stream data from medical devices. Medical data streams have become widespread and call for development of intelligent tools for making use of these data. Decision support, alerting services, ambient intelligence, assisted leaving and personalization services are just few examples of expected uses of actionable knowledge extracted from medical data streams. All of them are characterized by the high-speed at which huge amounts of data are produced, and often require fast and accurate information retrieval and analysis, that can effectively support clinical decisions.

Dealing with continuous, and possibly infinite, flows of data require different approaches for data processing and management, and further machine learning and knowledge discovery. Particular issues to address include summarization of infinite data, incremental and decremental learning, resource-awareness, real-time monitoring of changes and recurrences, etc. This is an incremental task that requires incremental algorithms that integrate very large data bases in medical domains. Streaming artificial intelligence is increasingly important in the research community, as new algorithms are needed to process medical data in reasonable time.

Furthermore, medical domains introduce extra peculiarities to the problem. For example, health information systems now deal with heterogeneous data sources, possibly distributed across health-care institutions. Moreover, this data integration requirement yields privacy-preserving issues. At the same time, it forces the system to take time, resources, and costs into consideration. Currently, generic techniques for intelligent analysis and learning from streaming data include also processing and management techniques which are widely spread in the applied computing research community. Also, in the medical domain, technological issues of data collection and storage, access, integration, information fusion, etc are also widely studied in the health informatics research community. However, adoption and development of tailored techniques for medical stream mining and clinical decision support is still to come.

The goal of this special issue is to present cutting-edge research from experts in data stream processing interested in medical applications and medical domain experts interested in timely analysis of their data streams for clinical decision support.

TOPICS

Topics include but are not restricted to processing, managing and knowledge discovery for:
Anatomical or physiological sensor data streams
Data streams in health-care
Integrating biomedical signals and electronic health records
Integrated health information data streams
Adaptive health information systems
Medical data stream models
Mobile and ubiquitous medical data streams
Data quality in medical data streams
Data streams integration in intensive care units
Remote monitoring of patients in hospital and ambulatory settings
Process mining from medical data streams
Case reports of medical scenarios where data is produced in a stream
Real-time and real-world applications using streaming medical data
Languages and ontologies for medical stream query
Integration with real-time enactment of clinical guidelines
Privacy and security issues in medical data streams

SPECIAL ISSUE GUEST EDITORS

Pedro Pereira Rodrigues - LIAAD & Faculty of Medicine, University of Porto, Portugal
Mykola Pechenizkiy - Eindhoven University of Technology, the Netherlands
Mohamed Medhat Gaber - University of Portsmouth, United Kingdom
Carolyn McGregor - University of Ontario Institute of Technology, Canada
João Gama - LIAAd & Faculty of Economics, University of Porto, Portugal

PAPER FORMATTING, SUBMISSION AND REVIEWING

Authors should follow the guide to authors available at AIIM website to format their article. Please note that, for the initial submission, only PDF format of submissions is allowed. Papers to this special issue should be submitted by email to the guest editors at pprodrigues@med.up.pt and not via the online Elsevier Editorial System.

Each paper submission will be peer-reviewed by at least three reviewers. The quest editors will screen the submissions for eligibility and quality. Special issue articles should report on significant previously unpublished work.

We do invite authors to submit their revised and substantially extended workshop and conference papers. As a rule of thumb the journal paper submission should contain at least 30% of new previously unpublished material. Please indicate in your cover letter whether the journal paper submission is based on or extend substantially a previously published conference or workshop paper, in case of which a description of what is new must be clarified in the submission.

All papers accepted to the special issue are subject to the final approval by the Editor-in-Chief of AIIM journal. It is planned that the articles will appear in one of the issues of the Artificial Intelligence in Medicine Journal, edited and published by Elsevier, in 2013. AIIM typically has 9 issues per year.

Call for Papers for a Special Issue of IEEE Transactions on Biomedical Engineering: Surgical Robotics

Submissions Due Date: June 1, 2012