Five-year experience with setup and implementation of an integrated database system for clinical documentation and research

In radiation oncology, where treatment concepts are elaborated in interdisciplinary collaborations, handling distributed, large heterogeneous amounts of data efficiently is very important, yet challenging, for an optimal treatment of the patient as well as for research itself. This becomes a strong focus, as we step into the era of modern personalized medicine, relying on various quantitative data information, thus involving the active contribution of multiple medical specialties. Hence, combining patient data from all involved information systems is inevitable for analyses. Therefore, we introduced a documentation and data management system integrated in the clinical environment for electronic data capture. We discuss our concept and five-year experience of a precise electronic documentation system, with special focus on the challenges we encountered. We specify how such a system can be designed and implemented to plan, tailor and conduct (multicenter) clinical trials, ultimately reaching the best clinical performance, and enhancing interdisciplinary and clinical research.     

Detection of colorectal adenoma and cancer based on transthyretin and C3a-desArg serum levels

Colorectal cancer is the second leading cause of cancer death, and it develops from benign colorectal adenomas in over 95% of patients. Early detection of these cancer precursors by screening tests and their removal can potentially eradicate more than 95% of colorectal cancers before they develop. To discover sensitive and specific biomarkers for improvement of pre‐clinical diagnosis of colorectal adenoma and cancer, we analysed in two independent studies (n = 87 and n = 83 patients) serum samples from colorectal cancer (stage III), colorectal adenoma and control patients using SELDI‐TOF‐MS. Extensive statistical analysis was performed to establish homogeneous patient groups based on their clinical data. Two biomarkers that were each able to distinguish control patients from either colorectal adenoma or colorectal cancer patients (p<0.001) were identified as transthyretin (pre‐albumin) and C3a‐desArg by MS/MS and were further validated by antibody‐based assays (radial immunodiffusion, ELISA). A combination of both proteins clearly indicated the presence of colorectal adenoma or carcinoma. Using a cut‐off of <0.225 g/L for transthyretin and >1974 ng/mL for C3a‐desArg, we found a sensitivity and specificity for colorectal adenoma of 96% and 70%, respectively.     

An internet of old things as an augmented memory system

The interdisciplinary Tales of Things and electronic Memory (TOTeM) project investigates new contexts for augmenting things with stories in the emerging culture of the Internet of Things (IoT). Tales of Things is a tagging system which, based on two-dimensional barcodes (also called Quick Response or QR codes) and Radio Frequency Identification (RFID) technology, enables the capturing and sharing of object stories and the physical linking to objects via read and writable tags. Within the context of our study, it has functioned as a technology probe which we employed with the aim to stimulate discussion and identify desire lines that point to novel design opportunities for the engagement with personal and social memories linked to everyday objects. In this paper, we discuss results from fieldwork with different community groups in the course of which seemingly any object could form the basis of a meaningful story and act as entry point into rich inherent ‘networks of meaning’. Such networks of meaning are often solely accessible for the owner of an object and are at risk of getting lost as time goes by. We discuss the different discourses that are inherent in these object stories and provide avenues for making these memories and meaning networks accessible and shareable. This paper critically reflects on Tales of Things as an example of an augmented memory system and discusses possible wider implications for the design of related systems.     

Learning effective color features for content based image retrieval in dermatology

We investigate the extraction of effective color features for a content-based image retrieval (CBIR) application in dermatology. Effectiveness is measured by the rate of correct retrieval of images from four color classes of skin lesions. We employ and compare two different methods to learn favorable feature representations for this special application: limited rank matrix learning vector quantization (LiRaM LVQ) and a Large Margin Nearest Neighbor (LMNN) approach. Both methods use labeled training data and provide a discriminant linear transformation of the original features, potentially to a lower dimensional space. The extracted color features are used to retrieve images from a database by a k-nearest neighbor search. We perform a comparison of retrieval rates achieved with extracted and original features for eight different standard color spaces. We achieved significant improvements in every examined color space. The increase of the mean correct retrieval rate lies between 10% and 27% in the range of k=1-25 retrieved images, and the correct retrieval rate lies between 84% and 64%. We present explicit combinations of RGB and CIE-Lab color features corresponding to healthy and lesion skin. LiRaM LVQ and the computationally more expensive LMNN give comparable results for large values of the method parameter κ of LMNN (κ≥25) while LiRaM LVQ outperforms LMNN for smaller values of κ. We conclude that feature extraction by LiRaM LVQ leads to considerable improvement in color-based retrieval of dermatologic images.     

SWOF - an open framework for shared workspaces to support different cooperation tasks

Computer supported collaborative work (CSCW) allows people to cooperate by computers from different places and at different times. To enable an easier integration of such collaborative components into web-based communities and portals, a Shared Workspace Open Framework (SWOF) was developed. This framework provides the basic features of shared workspaces and can be customized to different cooperation cases. High usability is an important aspect of the implementation. To achieve these aims SWOF focuses on an information space with more task-suited item-types that can help to pre-structure the information. Thus, on the one hand the system can help the users to write down the needed information in a consistent way and, on the other, could reduce the arguments between the group members on how to structure their workspace. As a use case for SWOF the development of a Web-based portal for the community of man-machine interaction was chosen. In the project MMI-Interaktiv, a portal is built with a SWOF-based shared workspace component. An evaluation for this use case is presented.     

Getting to know each other—Artificial social intelligence for autonomous robots

This paper proposes a research direction to study the development of ‘artificial social intelligence’ of autonomous robots which should result in ‘individualized robot societies’. The approach is highly inspired by the ‘social intelligence hypothesis’, derived from the investigation of primate societies, suggesting that primate intelligence originally evolved to solve social problems and was only later extended to problems outside the social domain. We suggest that it might be a general principle in the evolution of intelligence, applicable to both natural and artificial systems. Arguments are presented why the investigation of social intelligence for artifacts is not only an interesting research issue for the study of biological principles, but may be a necessary prerequisite for those scenarios in which autonomous robots are integrated into human societies, interacting and communicating both with humans and with each other. As a starting point to study experimentally the development of robots' ‘social relationships’, the investigation of collection and use of body images by means of imitation is proposed. A specific experimental setup which we use to test the theoretical considerations is described. The paper outlines in what kind of applications and for what kind of robot group structures social intelligence might be advantageous.     

Investigation into TRIP steels won steel research Best Paper Award 1999

Research results are commonly circulated on the occasion of congresses or by publication in technical journals. steel research, the scientific journal edited by the Verein Deutscher Eisenhüttenleute, VDEh ‐ The German Iron and Steel Institute, and the Max‐Planck‐Institut für Eisenforschung, MPI, presents the latest results of fundamental research in the fields of process metallurgy, metal working and materials science as far as the material steel is concerned. Formerly well‐known as ?Archiv für das Eisenhüttenwesen“, steel research looks back on 70 years of experience in worldwide exchange of technological basics. In 1995, the editors decided to offer a Best Paper Award with 1.000 US‐$ purse and a pretty diploma. This year, it was for the fifth time that authors have been awarded with the steel research Best Paper Award. The Editorial Board has chosen a contribution to TRIP steels from the papers published in the 1999 annual volume.     

涂层辊筒技术——非织造布整理用涂层辊简装置的多功能工艺理念

单面低加料率的涂层辊筒装置应用在非织造布工业中有着悠久的历史,绝大多数用于非织造尿布顶层的低加料率,单面亲水或永久亲水.Andritz Ktisters(安德里兹寇司德)为进行高速生产的非织造布工业客户(速度高至1000m/min)提供量身定做的neXkiss涂层辊筒产品系列.最新开发的neXkiss plus拥有特殊的灵活性和最大的生产多功能性.