Building Data-Driven Pathways From Routinely Collected Hospital Data:A Case Study on Prostate Cancer

Background: Routinely collected data in hospitals is complex, typically heterogeneous, and scattered across multiple Hospital Information Systems (HIS). This big data, created as a byproduct of health care activities, has the potential to provide a better understanding of diseases, unearth hidden patterns, and improve services and cost. The extent and uses of such data rely on its quality, which is not consistently checked, nor fully understood. Nevertheless, using routine data for the construction of data-driven clinical pathways, describing processes and trends, is a key topic receiving increasing attention in the literature. Traditional algorithms do not cope well with unstructured processes or data, and do not produce clinically meaningful visualizations. Supporting systems that provide additional information, context, and quality assurance inspection are needed. Objective: The objective of the study is to explore how routine hospital data can be used to develop data-driven pathways that describe the journeys that patients take through care, and their potential uses in biomedical research; it proposes a framework for the construction, quality assessment, and visualization of patient pathways for clinical studies and decision support using a case study on prostate cancer. Methods: Data pertaining to prostate cancer patients were extracted from a large UK hospital from eight different HIS, validated, and complemented with information from the local cancer registry. Data-driven pathways were built for each of the 1904 patients and an expert knowledge base, containing rules on the prostate cancer biomarker, was used to assess the completeness and utility of the pathways for a specific clinical study. Software components were built to provide meaningful visualizations for the constructed pathways. Results: The proposed framework and pathway formalism enable the summarization, visualization, and querying of complex patient-centric clinical information, as well as the computation of quality indicators and dimensions. A novel graphical representation of the pathways allows the synthesis of such information. Conclusions: Clinical pathways built from routinely collected hospital data can unearth information about patients and diseases that may otherwise be unavailable or overlooked in hospitals. Data-driven clinical pathways allow for heterogeneous data (ie, semistructured and unstructured data) to be collated over a unified data model and for data quality dimensions to be assessed. This work has enabled further research on prostate cancer and its biomarkers, and on the development and application of methods to mine, compare, analyze, and visualize pathways constructed from routine data. This is an important development for the reuse of big data in hospitals

Anticancer Activity of Uncommon Medicinal Plants from the Republic of Suriname: Traditional Claims, Preclinical Findings, and Potential Clinical Applicability against Cancer

Despite much progress in our understanding of the essence of cancer, remarkable advances in methods for early diagnosis, the expanding array of antineoplastic drugs and treatment modalities, as well as important refinements in their use, this disease is among the leading causes of morbidity and mortality in many parts of the world. In fact, the next decade is anticipated to bring over 20 million new cases per year globally, about half of whom will die from their disease. This indicates a need for better strategies to deal with cancer. One way to go forward is to draw lessons from ancient ethnopharmacological wisdom and to evaluate the plant biodiversity for compounds with potential antineoplastic activity. This approach has already yielded many breakthrough cytotoxic drugs such as vincristine, etoposide, paclitaxel, and irinotecan. The Republic of Suriname (South America), renowned for its pristine and highly biodiverse rain forests as well as its ethnic, cultural, and ethnopharmacological diversity, could also contribute to these developments. This chapter addresses the cancer problem throughout the world and in Suriname, extensively deals with nine plants used for treating cancer in the country, and concludes with their prospects in anticancer drug discovery and development programs

Under pressure: evolutionary engineering of yeast strains for improved performance in fuels and chemicals production.

Evolutionary engineering, which uses laboratory evolution to select for industrially relevant traits, is a popular strategy in the development of high-performing yeast strains for industrial production of fuels and chemicals. By integrating whole-genome sequencing, bioinformatics, classical genetics and genome-editing techniques, evolutionary engineering has also become a powerful approach for identification and reverse engineering of molecular mechanisms that underlie industrially relevant traits. New techniques enable acceleration of in vivo mutation rates, both across yeast genomes and at specific loci. Recent studies indicate that phenotypic trade-offs, which are often observed after evolution under constant conditions, can be mitigated by using dynamic cultivation regimes. Advances in research on synthetic regulatory circuits offer exciting possibilities to extend the applicability of evolutionary engineering to products of yeasts whose synthesis requires a net input of cellular energy

The effect of orientation of retinal configuration upon accommodation and convergence

The effect of orientation of retinal configuration upon accommodation and convergenc

Sustained, multifaceted improvements in mental well-being following psychedelic experiences in a prospective opportunity sample

In the last 15 years, psychedelic substances, such as LSD and psilocybin, have regained legitimacy in clinical research. In the general population as well as across various psychiatric populations, mental well-being has been found to significantly improve after a psychedelic experience. Mental well-being has large socioeconomic relevance, but it is a complex, multifaceted construct. In this naturalistic observational study, a comprehensive approach was taken to assessing well-being before and after a taking a psychedelic compound to induce a “psychedelic experience.” Fourteen measures of well-being related constructs were included in order to examine the breadth and specificity of change in well-being. This change was then analysed to examine clusters of measures changing together. Survey data was collected from volunteers that intended to take a psychedelic. Four key time points were analysed: 1 week before and 2 weeks, 4 weeks, and 2 years after the experience (N = 654, N = 315, N = 212, and N = 64, respectively). Change on the included measures was found to cluster into three factors which we labelled: 1) “Being well”, 2) “Staying well,” and 3) “Spirituality.” Repeated Measures Multivariate Analysis of Variance revealed all but the spirituality factor to be improved in the weeks following the psychedelic experience. Additional Mixed model analyses revealed selective increases in Being Well and Staying Well (but not Spirituality) that remained statistically significant up to 2 years post-experience, albeit with high attrition rates. Post-hoc examination suggested that attrition was not due to differential acute experiences or mental-health changes in those who dropped out vs. those who did not. These findings suggest that psychedelics can have a broad, robust and sustained positive impact on mental well-being in those that have a prior intention to use a psychedelic compound. Public policy implications are discussed

Visualization and Analysis Techniques for Three Dimensional Information Acquired by Confocal Microscopy

Confocal Scanning Laser Microscopy (CSLM) is particularly well suited for the acquisition of 3-dimensional data of microscopic objects. In the CSLM a specific volume in the object is sampled during the imaging process and the result is stored in a digital computer as a three-dimensional memory array. Optimal use of these data requires both the development of effective visual representations as well as analysis methods. In addition to the well known stereoscopic representation method a number of alternatives for various purposes are presented. When rendering in terms of solid-looking or semitransparent objects is required, an algorithm based on a simulated process of excitation and fluorescence is very suitable. Graphic techniques can be used to examine the 3-dimensional shape of surfaces. For (near-)real time applications a representation method should not require extensive previous data-processing or analysis. From the very extensive field of 3-D image analysis two examples are given

Australian Sphingidae – DNA Barcodes Challenge Current Species Boundaries and Distributions

© 2014 Rougerie et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The attached file is the published version of the article

Automated team selection and compliance checking in business processes

Plenty of activities in many business contexts must be performed collaboratively, e.g., in a hospital or when organising a conference. Tasks such as team composition and allocation are usually performed manually and on the ground of limited criteria such as individual skills, a.o. because adequate automatic support is missing. This paper addresses this shortcoming. We present an approach for team selection and compliance checking in business processes, which includes (i) a language for describing teams; (ii) a way to de- ne team selection conditions and policies related to team composition; and (iii) a mechanism for the automatic resolution of the team selection conditions and for team-related compliance checking based on formal ontologies.Austrian Research Funding Association (FFG) 845638 (SHAPE)Ministerio de Ciencia e Innovación TIN2009-07366 (SETI)Ministerio de Economía y Competitividad TIN2012-32273 (TAPAS)Junta de Andalucía TIC-5906 (THEOS