CARDIOCARE: An integrated platform for the management of elderly multimorbid patients with breast cancer therapy induced cardiac toxicity.

Breast cancer (BC) remains the most diagnosed cancer in women, accounting for 12% of new annual cancer cases in Europe and worldwide. Advances in surgery, radiotherapy and systemic treatment have resulted in improved clinical outcomes and increased survival rates in recent years. However, BC therapy-related cardiotoxicity, may severely impact short- and long-term quality of life and survival. This study presents the CARDIOCARE platform and its main components, which by integrating patient-specific data from different categories, data from patient-oriented eHealth applications and wearable devices, and by employing advanced data mining and machine learning approaches, provides the healthcare professionals with a valuable tool for effectively managing BC patients and preventing or alleviating treatment induced cardiotoxicity.Clinical Relevance- Through the adoption of CARDIOCARE platform healthcare professionals are able to stratify patients for their risk for cardiotoxicity and timely apply adequate interventions to prevent its onset.

Facial geometry and speech analysis for depression detection.

Depression is one of the most prevalent mental disorders, burdening many people world-wide. A system with the potential of serving as a decision support system is proposed, based on novel features extracted from facial expression geometry and speech, by interpreting non-verbal manifestations of depression. The proposed system has been tested both in gender independent and gender based modes, and with different fusion methods. The algorithms were evaluated for several combinations of parameters and classification schemes, on the dataset provided by the Audio/Visual Emotion Challenge of 2013 and 2014. The proposed framework achieved a precision of 94.8% for detecting persons achieving high scores on a self-report scale of depressive symptomatology. Optimal system performance was obtained using a nearest neighbour classifier on the decision fusion of geometrical features in the gender independent mode, and audio based features in the gender based mode; single visual and audio decisions were combined with the OR binary operation.

Integrating Microarray Data and GRNs.

With the completion of the Human Genome Project and the emergence of high-throughput technologies, a vast amount of molecular and biological data are being produced. Two of the most important and significant data sources come from microarray gene-expression experiments and respective databanks (e,g., Gene Expression Omnibus-GEO (http://www.ncbi.nlm.nih.gov/geo)), and from molecular pathways and Gene Regulatory Networks (GRNs) stored and curated in public (e.g., Kyoto Encyclopedia of Genes and Genomes-KEGG (http://www.genome.jp/kegg/pathway.html), Reactome (http://www.reactome.org/ReactomeGWT/entrypoint.html)) as well as in commercial repositories (e.g., Ingenuity IPA (http://www.ingenuity.com/products/ipa)). The association of these two sources aims to give new insight in disease understanding and reveal new molecular targets in the treatment of specific phenotypes.Three major research lines and respective efforts that try to utilize and combine data from both of these sources could be identified, namely: (1) de novo reconstruction of GRNs, (2) identification of Gene-signatures, and (3) identification of differentially expressed GRN functional paths (i.e., sub-GRN paths that distinguish between different phenotypes). In this chapter, we give an overview of the existing methods that support the different types of gene-expression and GRN integration with a focus on methodologies that aim to identify phenotype-discriminant GRNs or subnetworks, and we also present our methodology.

Extraction of facial features as indicators of stress and anxiety.

Stress and anxiety heavily affect the human wellbeing and health. Under chronic stress, the human body and mind suffers by constantly mobilizing all of its resources for defense. Such a stress response can also be caused by anxiety. Moreover, excessive worrying and high anxiety can lead to depression and even suicidal thoughts. The typical tools for assessing these psycho-somatic states are questionnaires, but due to their shortcomings, by being subjective and prone to bias, new more robust methods based on facial expression analysis have emerged. Going beyond the typical detection of 6 basic emotions, this study aims to elaborate a set of facial features for the detection of stress and/or anxiety. It employs multiple methods that target each facial region individually. The features are selected and the classification performance is measured based on a dataset consisting 23 subjects. The results showed that with feature sets of 9 and 10 features an overall accuracy of 73% is reached.

Vision-based absence seizure detection.

In order to diagnose epilepsy, neurologists rely on their experience, performing an equal assessment of the electroencephalogram and the clinical image. Since misdiagnosis reaches a rate of 30% and more than one-third of all epilepsies are poorly understood, a need for leveraging diagnostic precision is obvious. With the aim at enhancing the clinical image assessment procedure, this paper evaluates the suitability of certain facial expression features for detecting and quantifying absence seizures. These features are extracted by means of time-varying signal analysis from signals that are gained by applying computer vision techniques, such as face detection, dense optical flow computation and averaging background subtraction. For the evaluation, video sequences of four patients with absence seizures are used. The classification performance of a C4.5 decision tree shows accuracies of up to 99.96% with a worst percentage of incorrectly classified instances of 0.14%.

Clinically driven design of multi-scale cancer models: the ContraCancrum project paradigm.

The challenge of modelling cancer presents a major opportunity to improve our ability to reduce mortality from malignant neoplasms, improve treatments and meet the demands associated with the individualization of care needs. This is the central motivation behind the ContraCancrum project. By developing integrated multi-scale cancer models, ContraCancrum is expected to contribute to the advancement of in silico oncology through the optimization of cancer treatment in the patient-individualized context by simulating the response to various therapeutic regimens. The aim of the present paper is to describe a novel paradigm for designing clinically driven multi-scale cancer modelling by bringing together basic science and information technology modules. In addition, the integration of the multi-scale tumour modelling components has led to novel concepts of personalized clinical decision support in the context of predictive oncology, as is also discussed in the paper. Since clinical adaptation is an inelastic prerequisite, a long-term clinical adaptation procedure of the models has been initiated for two tumour types, namely non-small cell lung cancer and glioblastoma multiforme; its current status is briefly summarized.

A semantically aware platform for the authoring and secure enactment of bioinformatics workflows.

Recent advances in the field of bioinformatics present a number of challenges in the secure and efficient management and analysis of biological data resources. Workflow technologies aim to assist scientists and domain experts in the design of complex, long running, data and computing intensive experiments that involve many data processing and analysis tasks with the objective of generating new knowledge or formulate new hypothesis. In this paper we present a bioinformatics workflow authoring and execution environment that intends to greatly facilitate the whole lifecycle of such experiments. Emphasis is given on the security and ethical requirements of these scenarios and the corresponding technological response. In addition we present our semantic framework used for supporting specific user-requirements related to the reasoning and inference capabilities of the environment.

'In silico' oncology for clinical decision making in the context of nephroblastoma.

The present paper outlines the initial version of the ACGT (Advancing Clinico-Genomic Trials) -- an Integrated Project, partly funded by the EC (FP6-2005-IST-026996)I-Oncosimulator as an integrated software system simulating in vivo tumour response to therapeutic modalities within the clinical trials environment aiming to support clinical decision making in individual patients. Cancer treatment optimization is the main goal of the system. The document refers to the technology of the system and the clinical requirements and the types of medical data needed for exploitation in the case of nephroblastoma. The outcome of an initial step towards the clinical adaptation and validation of the system is presented and discussed. Use of anonymized real data before and after chemotherapeutic treatment for the case of the SIOP 2001/GPOH nephroblastoma clinical trial constitutes the basis of the clinical adaptation and validation process. By using real medical data concerning nephroblastoma for a single patient in conjunction with plausible values for the model parameters (based on available literature) a reasonable prediction of the actual tumour volume shrinkage has been made possible. Obviously as more and more sets of medical data are exploited the reliability of the model "tuning" is expected to increase. The successful performance of the initial combined ACGT Oncosimulator platform, although usable up to now only as a test of principle, has been a particularly encouraging step towards the clinical translation of the system, being the first of its kind worldwide.

Functional specifications of an integrated proteomics information management and analysis platform.

Detecting proteins in human blood holds the promise of a revolution in cancer diagnosis. Also, the ability to perform laboratory operations on small scales using miniaturized (lab-on-a-chip) devices has many benefits. Designing and fabricating such systems is extremely challenging, but physicists and engineers are beginning to construct such highly integrated and compact labs on chips with exciting functionality. This paper focuses on the presentation of the requirements of the information technology layer in such an integrated platform been developed in the LOCCANDIA project. LOCCANDIA is a Specific Targeted Research project (STREP) funded under the 6th Framework program of the EC. Its ultimate objective is to develop an innovative nano-technology based (lab-on-a-chip) platform for the medical-proeomics field. The paper presents the main engineering aspects, challenges and architecture for creating an Integrated Clinico-Proteomic Environment. The environment will be used to monitor and document the analysis and discovery chain and to allow the physician to interpret the digital spectrogram data delivered by the mass spectrometer, for diagnostic purposes.

Evaluation of shared EHR services in primary healthcare centers and their rural community offices: the twister story.

Ten years after primary, secondary, and tertiary healthcare facilities in Crete were connected in HYGEIAnet, one of the first regional health information networks worldwide, the Twister project addressed the practical challenge of delivering integrated eHealth services to remote healthcare facilities in Crete and the south Aegean. A hybrid network infrastructure comprising terrestrial broadband, wireless, and satellite segments provided connectivity among distributed healthcare organizations. A fast-track methodology of continuous training and evaluation was used to encourage the wide adoption of EHR services in primary healthcare centers and their remote community offices, eTraining in prehospital emergency management, and medical collaboration. For the evaluation of Twister, health professionals using EHRs and citizens visiting the healthcare facilities provided their attitudes and perceptions on eHealth. Although eHealth is viewed differently by citizens and health professionals, both groups consider the EHR as an important part of the daily medical practice. However, continuous training, practical incentives, and awareness initiatives are necessary to increase the use of EHRs and the social embedding of eHealth in rural areas.

Developing a European grid infrastructure for cancer research: vision, architecture and services.

Life sciences are currently at the centre of an information revolution. The nature and amount of information now available opens up areas of research that were once in the realm of science fiction. During this information revolution, the data-gathering capabilities have greatly surpassed the data-analysis techniques. Data integration across heterogeneous data sources and data aggregation across different aspects of the biomedical spectrum, therefore, is at the centre of current biomedical and pharmaceutical R&D.This paper reports on original results from the ACGT integrated project, focusing on the design and development of a European Biomedical Grid infrastructure in support of multi-centric, post-genomic clinical trials (CTs) on cancer. Post-genomic CTs use multi-level clinical and genomic data and advanced computational analysis and visualization tools to test hypotheses in trying to identify the molecular reasons for a disease and the stratification of patients in terms of treatment.The paper provides a presentation of the needs of users involved in post-genomic CTs and presents indicative scenarios, which drive the requirements of the engineering phase of the project. Subsequently, the initial architecture specified by the project is presented, and its services are classified and discussed. A range of such key services, including the Master Ontology on sCancer, which lie at the heart of the integration architecture of the project, is presented. Special efforts have been taken to describe the methodological and technological framework of the project, enabling the creation of a legally compliant and trustworthy infrastructure. Finally, a short discussion of the forthcoming work is included, and the potential involvement of the cancer research community in further development or utilization of the infrastructure is described.

Building a European biomedical grid on cancer: the ACGT Integrated Project.

This paper presents the needs and requirements that led to the formation of the ACGT (Advancing Clinico Genomic Trials) integrated project, its vision and methodological approaches of the project. The ultimate objective of the ACGT project is the development of a European biomedical grid for cancer research, based on the principles of open access and open source, enhanced by a set of interoperable tools and services which will facilitate the seamless and secure access to and analysis of multi-level clinico-genomic data, enriched with high-performing knowledge discovery operations and services. By doing so, it is expected that the influence of genetic variation in oncogenesis will be revealed, the molecular classification of cancer and the development of individualised therapies will be promoted, and finally the in-silico tumour growth and therapy response will be realistically and reliably modelled. Its main design decisions and results at its current stage of development are presented.

Automatic labelling and BI-RADS characterisation of mammogram densities.

Intelligent management of medical data is an important field of research in clinical information and decision support systems. Such systems are finding increasing use in the management of patients known to have, or suspected of having, breast cancer. Different types of breast-tissue patterns convey semantic information which is reported by the radiologist when reading mammograms. In this paper, a novel method is presented for the automatic labelling and characterisation of mammographic densities. The presented method is first concerned with the identification of the prominent structures in each mammogram. Subsequently, "dense tissue" is labelled in a mammogram data set, and BI-RADS classification is performed based on a 2D pdf that is contracted from a "ground truth" data set as well as a shape analysis framework. The presented method can be used in large-scale epidemiological studies which involve mammographic measurements of tissue-pattern, especially since breast-tissue density has been linked to an increased risk of breast cancer.

JUST in time health emergency interventions: an innovative approach to training the citizen for emergency situations using virtual reality techniques and advanced IT tools (the Web-CD).

This paper reports the results of the first of the two systems developed by JUST, a collaborative project supported by the European Union under the Information Society Technologies (IST) Programme. The most innovative content of the project has been the design and development of a complementary training course for non-professional health emergency operators, which supports the traditional learning phase, and which purports to improve the retention capability of the trainees. This was achieved with the use of advanced information technology techniques, which provide adequate support and can help to overcome the present weaknesses of the existing training mechanisms.

JUST in time health emergency interventions: an innovative approach to training the citizen for emergency situations using virtual reality techniques and advanced IT tools (the VR Tool).

This paper reports the results of the second of the two systems developed by JUST, a collaborative project supported by the European Union under the Information Society Technologies (IST) Programme. The most innovative content of the project has been the design and development of a complementary training course for non-professional health emergency operators, which supports the traditional learning phase, and which purports to improve the retention capability of the trainees. This was achieved with the use of advanced information technology techniques, which provide adequate support and can help to overcome the present weaknesses of the existing training mechanisms.

An infrastructure for Integrated Electronic Health Record services: the role of XML (Extensible Markup Language).

BACKGROUND: The sharing of information resources is generally accepted as the key to substantial improvements in productivity and better quality of care. In addition, due to the greater mobility of the population, national and international healthcare networks are increasingly used to facilitate the sharing of healthcare-related information among the various actors of the field. In the context of HYGEIAnet, the regional health telematics network of Crete, an Integrated Electronic Health Record environment has been developed to provide integrated access to online clinical information, accessible throughout the island. OBJECTIVES: To make available comprehensive medical information about a patient by means of incorporating all the distributed and heterogeneous health record segments into an Integrated Electronic Health Record that can be viewed on-line through a unified user interface and visualization environment. METHODS: The technological approach for implementing this Integrated Electronic Health Record environment is based on the HYGEIAnet Reference Architecture, which provides the necessary framework for the reuse of services, components, and interfaces. Seamless presentation of information is achieved by means of the Extensible Markup Language (XML), while its underlying capabilities allow for dynamic navigation according to personalized end-user preferences and authorities. RESULTS: The Integrated Electronic Health Record environment developed in HYGEIAnet provides the basis for consistent and authenticated access to primary information over the Internet in order to support decision-making. Primary information is always kept at the place where it has been produced, and is maintained by the most appropriate clinical information system, contrasting traditional store and forward techniques, or centralized clinical data repositories. CONCLUSIONS: Since documents are much more easily accessible rather than data inside a database, Extensible Markup Language has the potential of becoming a very cheap technology provided, of course, that the underlying Healthcare Information Infrastructure exists. XML can be introduced incrementally and its implementation is completely transparent to the end user.

An open, component-based information infrastructure to support integrated regional healthcare networks.

A fundamental requirement for achieving continuity of care is the seamless sharing of multi-clinical information. Several different technological approaches can be followed to enable the sharing of health record segments. In all cases interoperability between systems is a prerequisite and this requires presently a major technological challenge. Inter-operability can be achieved either through messages or through a more advanced approach based on a federation of autonomous systems. Message based integration is centered mainly on the exchange of HL7 and DICOM messages for achieving the functional integration of clinical information systems (CIS) at institutional or regional level. The federated approach is principally used for facilitating the virtual view of the Integrated Electronic Health Record (I-EHR), without having to replicate unnecessary information. Within the context of HYGEIAnet, which is the regional health telematics network of Crete, both approaches have been utilized for providing end users with seamless access to clinical information. Both are based on an open architecture, which provides the framework for the reuse of standardized common components and public interfaces. This work presents the experiences related to the implementation of "messaging" and "federating" in HYGEIAnet, which are used complementary to each other. A comparison of the two parallel approaches, together with their strengths and weaknesses is described, and evaluation is given from the technological as well as the end users' perspective. Emphasis is given on the technological challenges in developing open, component-based information infra-structure to support integrated service delivery.

Role-based access to patients clinical data: the InterCare approach in the region of Crete.

The basics of a particular Integrated Electronic Health Record (I-EHR) implementation are presented, as realised by the Patient Clinical Data Directory (PCDD) system. PCDD operates within the context of HYGEIAnet, the Integrated Healthcare Telematics Network of Crete. PCDD is based on a federation of autonomous information systems and provides to its authorized users alternative views of the health record as well as access and retrieval services to its geographically distributed segments. The data model of the PCDD is based on the Subjective Objective Assessment Plan (SOAP) model that originates from the primary healthcare domain. Access to detailed information on particular patients healthcare encounters is delivered via role-based authorization privileges and controls. The administration of the national healthcare organizations' business rules, for different user-groups, is made via a specially tailored and developed rule-editor.

Functional and control integration of an ICU, LIS and PACS information system.

The need for collaboration and data sharing among systems dedicated to individual functional areas and user groups has initiated major efforts towards the development of an integrated hospital information system. Major issues in the development of any integrated architecture that incorporates autonomous departmental systems include the development of commonly accepted interaction mechanisms, standardisation, the structure of the computerised patient record, its extensibility, as well as limitations multimedia data impose. This paper presents work done within project IHIS, a nationally funded project for the development of an integrated hospital information system that provides ICU staff with access to both the ICU assisting laboratory information system's data as well as radiological multimedia data.