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Journal articles on the topic 'Common Workflow Language'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Suetake, Hirotaka, Tomoya Tanjo, Manabu Ishii, et al. "Sapporo: A workflow execution service that encourages the reuse of workflows in various languages in bioinformatics." F1000Research 11 (August 4, 2022): 889. http://dx.doi.org/10.12688/f1000research.122924.1.

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The increased demand for efficient computation in data analysis encourages researchers in biomedical science to use workflow systems. Workflow systems, or so-called workflow languages, are used for the description and execution of a set of data analysis steps. Workflow systems increase the productivity of researchers, specifically in fields that use high-throughput DNA sequencing applications, where scalable computation is required. As systems have improved the portability of data analysis workflows, research communities are able to share workflows to reduce the cost of building ordinary analy

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Clarke, Daniel J. B., John Erol Evangelista, Zhuorui Xie, et al. "Playbook workflow builder: Interactive construction of bioinformatics workflows." PLOS Computational Biology 21, no. 4 (2025): e1012901. https://doi.org/10.1371/journal.pcbi.1012901.

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The Playbook Workflow Builder (PWB) is a web-based platform to dynamically construct and execute bioinformatics workflows by utilizing a growing network of input datasets, semantically annotated API endpoints, and data visualization tools contributed by an ecosystem of collaborators. Via a user-friendly user interface, workflows can be constructed from contributed building-blocks without technical expertise. The output of each step of the workflow is added into reports containing textual descriptions, figures, tables, and references. To construct workflows, users can click on cards that repres

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Kale, Amruta, Ziheng Sun, Chao Fan, and Xiaogang Ma. "Geoweaver_cwl: Transforming geoweaver AI workflows to common workflow language to extend interoperability." Applied Computing and Geosciences 19 (September 2023): 100126. http://dx.doi.org/10.1016/j.acags.2023.100126.

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Zulfiqar, Mahnoor, Michael R. Crusoe, Birgitta König-Ries, Christoph Steinbeck, Kristian Peters, and Luiz Gadelha. "Implementation of FAIR Practices in Computational Metabolomics Workflows—A Case Study." Metabolites 14, no. 2 (2024): 118. http://dx.doi.org/10.3390/metabo14020118.

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Scientific workflows facilitate the automation of data analysis tasks by integrating various software and tools executed in a particular order. To enable transparency and reusability in workflows, it is essential to implement the FAIR principles. Here, we describe our experiences implementing the FAIR principles for metabolomics workflows using the Metabolome Annotation Workflow (MAW) as a case study. MAW is specified using the Common Workflow Language (CWL), allowing for the subsequent execution of the workflow on different workflow engines. MAW is registered using a CWL description on Workfl

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Iacopo, Colonnelli, Aldinucci Marco, Cantalupo Barbara, and al. et. "Distributed workflows with Jupyter." Future generation computer systems 128 (March 1, 2022): pp. 282–298. https://doi.org/10.1016/j.future.2021.10.007.

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The designers of a new coordination interface enacting complex workflows have to tackle a dichotomy: choosing a language-independent or language-dependent approach. Language-independent approaches decouple workflow models from the host code’s business logic and advocate portability. Language-dependent approaches foster flexibility and performance by adopting the same host language for business and coordination code. Jupyter Notebooks, with their capability to describe both imperative and declarative code in a unique format, allow taking the best of the two approaches, maintaining a clear

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Farah, Zaib Khan, Soiland-Reyes Stian, O. Sinnott Richard, Lonie Andrew, Goble Carole, and R. Crusoe Michael. "Sharing interoperable workflow provenance: A review of best practices and their practical application in CWLProv." GigaScience 8, no. 11 (2019): giz095. https://doi.org/10.5281/zenodo.3528059.

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<strong>Background</strong> The automation of data analysis in the form of <em>scientific workflows</em> has become a widely adopted practice in many fields of research. Computationally driven data-intensive experiments using workflows enable automation, scaling, adaptation, and provenance support. However, there are still several challenges associated with the effective sharing, publication, and reproducibility of such workflows due to the incomplete capture of provenance and lack of interoperability between different technical (software) platforms. <strong>Results</strong> Based on best-prac

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Jackson, Michael, Kostas Kavoussanakis, and Edward W. J. Wallace. "Using prototyping to choose a bioinformatics workflow management system." PLOS Computational Biology 17, no. 2 (2021): e1008622. http://dx.doi.org/10.1371/journal.pcbi.1008622.

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Workflow management systems represent, manage, and execute multistep computational analyses and offer many benefits to bioinformaticians. They provide a common language for describing analysis workflows, contributing to reproducibility and to building libraries of reusable components. They can support both incremental build and re-entrancy—the ability to selectively re-execute parts of a workflow in the presence of additional inputs or changes in configuration and to resume execution from where a workflow previously stopped. Many workflow management systems enhance portability by supporting th

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Plesniewicz, Gerald, and Baurzhan Karabekov. "Specifying temporal knowledge for workflows ontologies." Open Computer Science 6, no. 1 (2016): 226–31. http://dx.doi.org/10.1515/comp-2016-0020.

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AbstractA workflow is an automation of a process, in which participants (people or programs) are involved in activities for solving a set of tasks according to certain rules and constraints in order to attain a common goal. The concept of workflow appeared in business informatics. Currently the workflow techniques are used in many other fields such as medical informatics, bioinformatics, automation of scientific research, computer-aided design and manufacturing, etc. An ontology is a formal description (in terms of concepts, entities, their properties and relationships) of knowledge for solvin

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FRANKAU, SIMON, DIOMIDIS SPINELLIS, NICK NASSUPHIS, and CHRISTOPH BURGARD. "Commercial uses: Going functional on exotic trades." Journal of Functional Programming 19, no. 1 (2009): 27–45. http://dx.doi.org/10.1017/s0956796808007016.

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AbstractThe Functional Payout Framework (fpf) is a Haskell application that uses an embedded domain-specific functional language to represent and process exotic financial derivatives. Whereas scripting languages for pricing exotic derivatives are common in banking, fpf uses multiple interpretations to not only price such trades, but also to analyse the scripts to provide lifecycle support and more. This paper discusses fpf in relation to the wider trading workflow and our experiences in using a functional language in such a system as both an implementation language and a domain-specific langua

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WYNN, M. T., W. M. P. VAN DER AALST, A. H. M. TER HOFSTEDE, and D. EDMOND. "SYNCHRONIZATION AND CANCELATION IN WORKFLOWS BASED ON RESET NETS." International Journal of Cooperative Information Systems 18, no. 01 (2009): 63–114. http://dx.doi.org/10.1142/s0218843009002002.

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Workflow languages offer constructs for coordinating tasks. Among these constructs are various types of splits and joins. One type of join, which shows up in various incarnations, is the OR-join. Different approaches assign a different (often only intuitive) semantics to this type of join, though they do share the common theme that branches that cannot complete will not be waited for. Many systems and languages struggle with the semantics and implementation of the OR-join because its non-local semantics require a synchronization depending on the analysis of future execution paths. The presence

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Lee, Soohyun, Jeremy Johnson, Carl Vitzthum, Koray Kırlı, Burak H. Alver, and Peter J. Park. "Tibanna: software for scalable execution of portable pipelines on the cloud." Bioinformatics 35, no. 21 (2019): 4424–26. http://dx.doi.org/10.1093/bioinformatics/btz379.

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Abstract Summary We introduce Tibanna, an open-source software tool for automated execution of bioinformatics pipelines on Amazon Web Services (AWS). Tibanna accepts reproducible and portable pipeline standards including Common Workflow Language (CWL), Workflow Description Language (WDL) and Docker. It adopts a strategy of isolation and optimization of individual executions, combined with a serverless scheduling approach. Pipelines are executed and monitored using local commands or the Python Application Programming Interface (API) and cloud configuration is automatically handled. Tibanna is w

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Zhang, Jiali. "AI Agents in Education: Four Trends and a Practical Workflow." Proceedings of the AAAI Symposium Series 5, no. 1 (2025): 131–32. https://doi.org/10.1609/aaaiss.v5i1.35578.

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AI agents based on large language models (LLMs) are transforming education by offering personalized tutoring, faster grading, innovative content generation, and streamlined administrative tasks. This paper explores four major trends of AI agents in the education industry: tutoring and mentoring, automated grading, content creation, and administrative automation. This study also introduces a common AI agent prototype, focusing on customization through fine-tuning and retrieval-augmented generation (RAG), and highlights the role of external tools in enhancing versatility. By reviewing current ap

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Xiao, Nan, Soner Koc, David Roberson, Phillip Brooks, Manisha Ray, and Dennis Dean. "BCO App: tools for generating BioCompute Objects from next-generation sequencing workflows and computations." F1000Research 9 (September 16, 2020): 1144. http://dx.doi.org/10.12688/f1000research.25902.1.

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The BioCompute Object (BCO) standard is an IEEE standard (IEEE 2791-2020) designed to facilitate the communication of next-generation sequencing data analysis with applications across academia, government agencies, and industry. For example, the Food and Drug Administration (FDA) supports the standard for regulatory submissions and includes the standard in their Data Standards Catalog for the submission of HTS data. We created the BCO App to facilitate BCO generation in a range of computational environments and, in part, to participate in the Advanced Track of the precisionFDA BioCompute Objec

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Thi Nhung, Doan, and Bui Van Ngoc. "Bioinformatic approaches for analysis of coral-associated bacteria using R programming language." Vietnam Journal of Biotechnology 18, no. 4 (2021): 733–43. http://dx.doi.org/10.15625/1811-4989/18/4/15320.

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Recent advances in metagenomics and bioinformatics allow the robust analysis of the composition and abundance of microbial communities, functional genes, and their metabolic pathways. So far, there has been a variety of computational/statistical tools or software for analyzing microbiome, the common problems that occurred in its implementation are, however, the lack of synchronization and compatibility of output/input data formats between such software. To overcome these challenges, in this study context, we aim to apply the DADA2 pipeline (written in R programming language) instead of using a

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Meyer, Folker, Saurabh Bagchi, Somali Chaterji, et al. "MG-RAST version 4—lessons learned from a decade of low-budget ultra-high-throughput metagenome analysis." Briefings in Bioinformatics 20, no. 4 (2017): 1151–59. http://dx.doi.org/10.1093/bib/bbx105.

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Abstract As technologies change, MG-RAST is adapting. Newly available software is being included to improve accuracy and performance. As a computational service constantly running large volume scientific workflows, MG-RAST is the right location to perform benchmarking and implement algorithmic or platform improvements, in many cases involving trade-offs between specificity, sensitivity and run-time cost. The work in [Glass EM, Dribinsky Y, Yilmaz P, et al. ISME J 2014;8:1–3] is an example; we use existing well-studied data sets as gold standards representing different environments and differen

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Hamilton, Joanna M., Debra McNeil, Dana Milne, et al. "Structuring clinical pathways: Creating common language where there is none." Journal of Clinical Oncology 37, no. 27_suppl (2019): 303. http://dx.doi.org/10.1200/jco.2019.37.27_suppl.303.

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303 Background: Clinical pathways (PW) consist of Decision Criteria (DC) such as patient and disease characteristics, prior therapy, and genetic tests. Historical Dana-Farber Pathways (DFP) content was unstructured and maintained in static documents. This could lead to inconsistencies across and within PW, limits to the scope of DFP analytics, and potential discrepancies in clinical content. Methods: To transform DFP content into a digitally innovative structure the DFP team created a hierarchical Data Model (DM). The team compiled all unstructured DC in historical PW, organized them into para

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Woolland, Oliver, Paul Brack, Stian Soiland-Reyes, Ben Scott, and Laurence Livermore. "Incrementally building FAIR Digital Objects with Specimen Data Refinery workflows." Research Ideas and Outcomes 8 (October 12, 2022): e94349. https://doi.org/10.3897/rio.8.e94349.

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<em>Specimen Data Refinery</em> (SDR) is a developing platform for automating transcription of specimens from natural history collections (Hardisty et al. 2022). SDR is based on computational workflows and digital twins using FAIR Digital Objects.We show our recent experiences with building SDR using the Galaxy workflow system and combining two FDO methodologies with open digital specimens (openDS) and RO-Crate data packaging. We suggest FDO improvements for incremental building of digital objects in computational workflows.SDR workflowsSDR is realised as the workflow system Galaxy (Afgan et a

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Hillion, Kenzo-Hugo, Ivan Kuzmin, Anton Khodak, et al. "Using bio.tools to generate and annotate workbench tool descriptions." F1000Research 6 (November 30, 2017): 2074. http://dx.doi.org/10.12688/f1000research.12974.1.

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Workbench and workflow systems such as Galaxy, Taverna, Chipster, or Common Workflow Language (CWL)-based frameworks, facilitate the access to bioinformatics tools in a user-friendly, scalable and reproducible way. Still, the integration of tools in such environments remains a cumbersome, time consuming and error-prone process. A major consequence is the incomplete or outdated description of tools that are often missing important information, including parameters and metadata such as publication or links to documentation. ToolDog (Tool DescriptiOn Generator) facilitates the integration of tool

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Torres Silva, Ever Augusto, Sebastian Uribe, Jack Smith, Ivan Felipe Luna Gomez, and Jose Fernando Florez-Arango. "XML Data and Knowledge-Encoding Structure for a Web-Based and Mobile Antenatal Clinical Decision Support System: Development Study." JMIR Formative Research 4, no. 10 (2020): e17512. http://dx.doi.org/10.2196/17512.

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Background Displeasure with the functionality of clinical decision support systems (CDSSs) is considered the primary challenge in CDSS development. A major difficulty in CDSS design is matching the functionality to the desired and actual clinical workflow. Computer-interpretable guidelines (CIGs) are used to formalize medical knowledge in clinical practice guidelines (CPGs) in a computable language. However, existing CIG frameworks require a specific interpreter for each CIG language, hindering the ease of implementation and interoperability. Objective This paper aims to describe a different a

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Cody, Hanson, and R. Walcott Kristen. "NETCDL : THE NETWORK CERTIFICATION DESCRIPTION LANGUAGE." International Journal of Computational Science, Information Technology and Control Engineering (IJCSITCE) 5, no. 3 (2019): 1–20. https://doi.org/10.5281/zenodo.3361024.

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Modern IP networks are complex entities that require constant maintenance and care. Similarly, constructing a new network comes with a high amount of upfront cost, planning, and risk. Unlike the disciplines of software and hardware engineering, networking and IT professionals lack an expressive and useful certification language that they can use to verify that their work is correct. When installing and maintaining networks without a standard for describing their behavior, teams find themselves prone to making configuration mistakes. These mistakes can have real monetary and operational efficie

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Minty, Gavin, Alex Hoppen, Ines Boehm, et al. "aNMJ-morph: a simple macro for rapid analysis of neuromuscular junction morphology." Royal Society Open Science 7, no. 4 (2020): 200128. http://dx.doi.org/10.1098/rsos.200128.

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Large-scale data analysis of synaptic morphology is becoming increasingly important to the field of neurobiological research (e.g. ‘connectomics’). In particular, a detailed knowledge of neuromuscular junction (NMJ) morphology has proven to be important for understanding the form and function of synapses in both health and disease. The recent introduction of a standardized approach to the morphometric analysis of the NMJ—‘NMJ-morph’—has provided the first common software platform with which to analyse and integrate NMJ data from different research laboratories. Here, we describe the design and

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Kołczyńska, Marta. "Combining multiple survey sources: A reproducible workflow and toolbox for survey data harmonization." Methodological Innovations 15, no. 1 (2022): 62–72. http://dx.doi.org/10.1177/20597991221077923.

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Ex-post harmonization of survey data creates new opportunities for research by extending the geographical and/or time coverage of analyses. Researchers increasingly combine data from different survey projects to analyze them as a single dataset, and while teams engaged in data harmonization continue to expand the information they provide to end users, there are still no commonly agreed standards for the documentation of data processing. Existing harmonization project typically opt for recode scripts that are generally hard to read, modify, and reuse, although some projects make efforts to faci

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Austin, Elizabeth J., Joseph A. Heim, Savitha Sangameswaran, Courtney Segal, Denise Chang, and Danielle C. Lavallee. "Augmenting systems-level implementation of patient-reported outcomes for depression care through the use of structured analysis and design technique." Implementation Research and Practice 3 (January 2022): 263348952211379. http://dx.doi.org/10.1177/26334895221137927.

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Background Health systems increasingly need to implement complex practice changes such as the routine capture of patient-reported outcome (PRO) measures. Yet, health systems have met challenges when trying to bring practice change to scale across systems at large. While implementation science can guide the evaluation of implementation determinants, teams first need tools to systematically understand and compare workflow activities across practice sites. Structured analysis and design technique (SADT), a system engineering method of workflow modeling, may offer an opportunity to enhance the sca

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WANG, SHU, ROUH-MEI HU, HAN C. W. HSIAO, et al. "USING SCDL FOR INTEGRATING TOOLS AND DATA FOR COMPLEX BIOMEDICAL APPLICATIONS." International Journal of Semantic Computing 02, no. 02 (2008): 291–308. http://dx.doi.org/10.1142/s1793351x08000476.

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Current bioinformatics tools or databases are very heterogeneous in terms of data formats, database schema, and terminologies. Additionally, most biomedical databases and analysis tools are scattered across different web sites making interoperability across such different services more difficult. It is desired that these diverse databases and analysis tools be normalized, integrated and encompassed with a semantic interface such that users of biological data and tools could communicate with the system in natural language and a workflow could be automatically generated and distributed into appr

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Pal, Soumitra, and Teresa M. Przytycka. "Bioinformatics pipeline using JUDI: Just Do It!" Bioinformatics 36, no. 8 (2019): 2572–74. http://dx.doi.org/10.1093/bioinformatics/btz956.

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Abstract Summary Large-scale data analysis in bioinformatics requires pipelined execution of multiple software. Generally each stage in a pipeline takes considerable computing resources and several workflow management systems (WMS), e.g. Snakemake, Nextflow, Common Workflow Language, Galaxy, etc. have been developed to ensure optimum execution of the stages across two invocations of the pipeline. However, when the pipeline needs to be executed with different settings of parameters, e.g. thresholds, underlying algorithms, etc. these WMS require significant scripting to ensure an optimal executi

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Li, HongYi, Jun-Fen Fu, and Andre Python. "Implementing Large Language Models in Health Care: Clinician-Focused Review With Interactive Guideline." Journal of Medical Internet Research 27 (July 11, 2025): e71916. https://doi.org/10.2196/71916.

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Background Large language models (LLMs) can generate outputs understandable by humans, such as answers to medical questions and radiology reports. With the rapid development of LLMs, clinicians face a growing challenge in determining the most suitable algorithms to support their work. Objective We aimed to provide clinicians and other health care practitioners with systematic guidance in selecting an LLM that is relevant and appropriate to their needs and facilitate the integration process of LLMs in health care. Methods We conducted a literature search of full-text publications in English on

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Vukojicic, Nevena, Aleksandar Danicic, Zelia Worman, et al. "Abstract 2075: Highly customizable multi-sample single cell RNA-Seq pipeline on the CGC." Cancer Research 83, no. 7_Supplement (2023): 2075. http://dx.doi.org/10.1158/1538-7445.am2023-2075.

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Abstract Single-cell (sc) transcriptomics has revolutionized our understanding of the biological characteristics and dynamics of cancer development. It can help us identify rare cell subpopulations and understand mechanisms associated with tumor genesis, progression, and response to therapy. The most important step in the analyses of any scRNA-seq dataset is subpopulation identification, usually performed via unsupervised clustering, followed by gene marker identification. We created a highly customizable workflow for sc data analysis, implemented in Common Workflow Language (CWL) on the Cance

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Thummerer, Tobias, Johannes Stoljar, and Lars Mikelsons. "NeuralFMU: Presenting a Workflow for Integrating Hybrid NeuralODEs into Real-World Applications." Electronics 11, no. 19 (2022): 3202. http://dx.doi.org/10.3390/electronics11193202.

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The term NeuralODE describes the structural combination of an Artificial Neural Network (ANN) and a numerical solver for Ordinary Differential Equations (ODE), the former acts as the right-hand side of the ODE to be solved. This concept was further extended by a black-box model in the form of a Functional Mock-up Unit (FMU) to obtain a subclass of NeuralODEs, named NeuralFMUs. The resulting structure features the advantages of the first-principle and data-driven modeling approaches in one single simulation model: a higher prediction accuracy compared to conventional First-Principle Models (FPM

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Bin Saran, Abdullah. "Künstliche Intelligenz und Sprachtechnologien im Bereich der Translation." Traduction et Langues 21, no. 2 (2022): 129–45. http://dx.doi.org/10.52919/translang.v21i2.910.

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Artificial Intelligence and Language Technologies in the Field of Translation  The present paper deals with the opportunities which language technologies and artificial intelligence might offer for translation professionals. The paper also examines and elucidates that these technologies might contain possible problems, hurdles and obstacles. But the researcher reinforces that they also possess the necessary skills, competencies and prerequisites for the successful implementation and use of these technologies as illustrated in the Literature Review and Discussion parts of this resea

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Van Der Haar (nee Kosten), Katarina, and Manouchehr Haghighi. "A new approach for production forecasting from individual layers in multi-layer commingled tight gas reservoirs." APPEA Journal 62, no. 2 (2022): S192—S195. http://dx.doi.org/10.1071/aj21119.

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Estimating future production in multi-layer tight gas reservoirs is necessary, but problematic. Initial production looks promising but soon decreases to levels that are much lower than first anticipated. Boundary-dominated flow to which common production data analysis can be applied to, takes up to 8 years to establish, yet future production estimations must be made at the time of drilling. Common industry software does not fully assess individual layer contribution because large uncertainties exist in layer-specific contributions to total production. Many engineers tend to use analysis method

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Ciangottini, Diego, Giulio Bianchini, Mirko Mariotti, Daniele Spiga, Loriano Storchi, and Giacomo Surace. "KServe inference extension for an FPGA vendor-free ecosystem." EPJ Web of Conferences 295 (2024): 11012. http://dx.doi.org/10.1051/epjconf/202429511012.

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Field Programmable Gate Arrays (FPGAs) are playing an increasingly important role in the sampling and data processing industry due to their intrinsically highly parallel architecture, low power consumption, and flexibility to execute custom algorithms. In particular, the use of FPGAs to perform Machine Learning (ML) inference is increasingly growing thanks to the development of High-Level Synthesis (HLS) projects that abstract the complexity of Hardware Description Language (HDL) programming. In this work we will describe our experience extending KServe predictors, an emerging standard for ML

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López-Fernández, Hugo, Osvaldo Graña-Castro, Alba Nogueira-Rodríguez, Miguel Reboiro-Jato, and Daniel Glez-Peña. "Compi: a framework for portable and reproducible pipelines." PeerJ Computer Science 7 (June 18, 2021): e593. http://dx.doi.org/10.7717/peerj-cs.593.

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Compi is an application framework to develop end-user, pipeline-based applications with a primary emphasis on: (i) user interface generation, by automatically generating a command-line interface based on the pipeline specific parameter definitions; (ii) application packaging, with compi-dk, which is a version-control-friendly tool to package the pipeline application and its dependencies into a Docker image; and (iii) application distribution provided through a public repository of Compi pipelines, named Compi Hub, which allows users to discover, browse and reuse them easily. By addressing thes

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Wang, Jingqi, Noor Abu-el-Rub, Josh Gray, et al. "COVID-19 SignSym: a fast adaptation of a general clinical NLP tool to identify and normalize COVID-19 signs and symptoms to OMOP common data model." Journal of the American Medical Informatics Association 28, no. 6 (2021): 1275–83. http://dx.doi.org/10.1093/jamia/ocab015.

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Abstract The COVID-19 pandemic swept across the world rapidly, infecting millions of people. An efficient tool that can accurately recognize important clinical concepts of COVID-19 from free text in electronic health records (EHRs) will be valuable to accelerate COVID-19 clinical research. To this end, this study aims at adapting the existing CLAMP natural language processing tool to quickly build COVID-19 SignSym, which can extract COVID-19 signs/symptoms and their 8 attributes (body location, severity, temporal expression, subject, condition, uncertainty, negation, and course) from clinical

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Epee-Bounya, Alexandra, Elizabeth Mari, Jahmakah-Lynn Seals, Shannon Regan, and Corinna J. Rea. "Improving Postpartum Depression Screening Rates Using a Quality Improvement Framework in a Community-based Academic Primary Care Clinic." Pediatric Quality & Safety 10, no. 2 (2025): e802. https://doi.org/10.1097/pq9.0000000000000802.

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Introduction: Maternal postpartum depression (PPD) is the most common diagnosis during the postpartum period, with a higher incidence in underserved populations. Though PPD often goes undiagnosed, prompt diagnosis has a positive impact on several measures of children’s health and development, as well as maternal health. To increase routine screening per American Academy of Pediatrics recommendations, we implemented a multipronged quality improvement (QI) initiative centered around a newborn coordinator embedded in our primary care clinic. Methods: A multidisciplinary team implemented a QI init

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Pesapane, Filippo, Priyan Tantrige, Paolo De Marco, et al. "Advancements in Standardizing Radiological Reports: A Comprehensive Review." Medicina 59, no. 9 (2023): 1679. http://dx.doi.org/10.3390/medicina59091679.

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Standardized radiological reports stimulate debate in the medical imaging field. This review paper explores the advantages and challenges of standardized reporting. Standardized reporting can offer improved clarity and efficiency of communication among radiologists and the multidisciplinary team. However, challenges include limited flexibility, initially increased time and effort, and potential user experience issues. The efforts toward standardization are examined, encompassing the establishment of reporting templates, use of common imaging lexicons, and integration of clinical decision suppo

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Agapito, Giuseppe, Marzia Settino, Francesca Scionti, et al. "DMETTM Genotyping: Tools for Biomarkers Discovery in the Era of Precision Medicine." High-Throughput 9, no. 2 (2020): 8. http://dx.doi.org/10.3390/ht9020008.

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The knowledge of genetic variants in genes involved in drug metabolism may be translated into reduction of adverse drug reactions, increase of efficacy, healthcare outcomes improvement and economic benefits. Many high-throughput tools are available for the genotyping of Single Nucleotide Polymorphisms (SNPs) known to be related to drugs and xenobiotics metabolism. DMETTM platform represents an example of SNPs panel to discover biomarkers correlated to efficacy or toxicity in common and rare diseases. The difficulty in analyzing the mole of information generated by DMETTM platform led to the de

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Weiland, Claus, Jonas Grieb, Daniel Bauer, et al. "Dataspace Integration for Agrobiodiversity Digital Twins with RO-Crate." Biodiversity Information Science and Standards 8 (August 12, 2024): e134479. https://doi.org/10.3897/biss.8.134479.

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A severe impact of human-induced climate change is the global decrease in crop yields, threatening the United Nations sustainable development goal (SDG) to end hunger, achieve food security, improve nutrition, and promote sustainable agriculture (SDG 2: "Zero Hunger Goal"). Decision-making on appropriate mitigation strategies requires data integration from heterogeneous data-rich contexts including Earth observation (EO), biodiversity monitoring, gene banks as well as socio-economic data. Accordingly, large-scale initiatives for thematic data spaces, such as the European projects Destination E

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Bravo, Michael, Felicia Paluck, Omar Taibah, et al. "34 Improving language concordant care in the paediatric emergency department." Paediatrics & Child Health 29, Supplement_1 (2024): e16-e16. http://dx.doi.org/10.1093/pch/pxae067.033.

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Abstract Background Paediatric patients and families with limited English proficiency (LEP) experience worse health outcomes. Use of professional medical interpreter services (IS) helps ensure that all patients receive high quality care, regardless of their preferred language of communication. Objectives The aim of this quality improvement (QI) study was to improve language concordant care within a paediatric emergency department (ED) in downtown Toronto by increasing the rate of over-the-phone interpreter use by 50% by July 2024 and to understand common reasons for interpreter non-use. Design

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Kodytek, Pavel, Alexandra Bodzas, and Jan Zidek. "Automated code development based on genetic programming in graphical programming language: A pilot study." PLOS ONE 19, no. 3 (2024): e0299456. http://dx.doi.org/10.1371/journal.pone.0299456.

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Continual technological advances associated with the recent automation revolution have tremendously increased the impact of computer technology in the industry. Software development and testing are time-consuming processes, and the current market faces a lack of specialized experts. Introducing automation to this field could, therefore, improve software engineers’ common workflow and decrease the time to market. Even though many code-generating algorithms have been proposed in textual-based programming languages, to the best of the authors’ knowledge, none of the studies deals with the impleme

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Leone, Simone, Francesco Lago, Doina Pisla, and Giuseppe Carbone. "A Systematic Approach for Robotic System Development." Technologies 13, no. 8 (2025): 316. https://doi.org/10.3390/technologies13080316.

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This paper introduces a unified and systematic design methodology for robotic systems that is generalizable across a wide range of applications. It integrates rigorous mathematical formalisms such as kinematics, dynamics, control theory, and optimization with advanced simulation tools, ensuring that each design decision is grounded in provable theory. The approach defines clear phases, including mathematical modeling, virtual prototyping, parameter optimization, and theoretical validation. Each phase builds on the previous one to reduce unforeseen integration issues. Spanning from conceptualiz

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Nanomi Arachchige, Isuri Anuradha, Priyadharshany Sandanapitchai, and Ruvan Weerasinghe. "Investigating Machine Learning & Natural Language Processing Techniques Applied for Predicting Depression Disorder from Online Support Forums: A Systematic Literature Review." Information 12, no. 11 (2021): 444. http://dx.doi.org/10.3390/info12110444.

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Depression is a common mental health disorder that affects an individual’s moods, thought processes and behaviours negatively, and disrupts one’s ability to function optimally. In most cases, people with depression try to hide their symptoms and refrain from obtaining professional help due to the stigma related to mental health. The digital footprint we all leave behind, particularly in online support forums, provides a window for clinicians to observe and assess such behaviour in order to make potential mental health diagnoses. Natural language processing (NLP) and Machine learning (ML) techn

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Emsley, Iain, and David De Roure. "A Framework for the Preservation of a Docker Container." International Journal of Digital Curation 12, no. 2 (2018): 125–35. http://dx.doi.org/10.2218/ijdc.v12i2.509.

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Reliably building and maintaining systems across environments is a continuing problem. A project or experiment may run for years. Software and hardware may change as can the operating system. Containerisation is a technology that is used in a variety of companies, such as Google, Amazon and IBM, and scientific projects to rapidly deploy a set of services repeatably. Using Dockerfiles to ensure that a container is built repeatably, to allow conformance and easy updating when changes take place are becoming common within projects. Its seen as part of sustainable software development. Containeris

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Yogesh, Rabadiya*1 Jignasha Dabhi2 Sanjay Chauhan3. "An Overview of Regulatory Management Software for Educational and Industrial Sectors." International Journal of Pharmaceutical Sciences 3, no. 2 (2025): 898–913. https://doi.org/10.5281/zenodo.14862201.

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The abstract presents an in-depth look at software solutions developed specifically for managing the Electronic Common Technical Document (eCTD) in the pharmaceutical and life sciences industries. These solutions are designed to optimize various aspects of regulatory document management, including document organization, validation, publishing, and submission tracking. By integrating with existing systems, they facilitate a seamless and efficient regulatory workflow, enabling organizations to streamline the submission process while adhering to regulatory standards. Key features of these solutio

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Pabon, Cindy M., Terri Earles, Jessica Jimenez-Abarca, et al. "Post-hospitalization oncology workflow implementing LACE+ score to stratify and reduce readmissions at Lyndon B. Johnson safety-net hospital." JCO Oncology Practice 19, no. 11_suppl (2023): 56. http://dx.doi.org/10.1200/op.2023.19.11_suppl.56.

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56 Background: Patients with cancer visit the emergency room (ER) and are hospitalized frequently. Contributing factors may include uncontrolled symptoms (cancer- or treatment-related), caregiver fatigue, concerns about the cancer, and difficulty accessing healthcare elsewhere. It is estimated that nearly 50% of ER and hospital visits by advanced cancer patients may be avoidable. This may represent unmet needs in oncology outpatient care and counseling. The LACE+ index is a validated clinical tool available within EPIC electronic medical record system to predict the risk of 30-day readmission.

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Melnikova, Antonina V., Marina S. Vorobeva, and Anna V. Glazkova. "Comparison of pre-trained models for domain-specific entity extraction from student report documents." Modeling and Analysis of Information Systems 32, no. 1 (2025): 66–79. https://doi.org/10.18255/1818-1015-2025-1-66-79.

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The authors propose a methodology for extracting domain-specific entities from student report documents in Russian language using pre-trained transformer-based language models. Extracting domain-specific entities from student report documents is a relevant task since the obtained data can be used for various purposes, ranging from the formation of project teams to the personalization of learning pathways. Additionally, automating the document processing workflow reduces the labor costs associated with manual processing. As training material for training models, expert-annotated student report

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Wiedemann, Gregor. "Proportional Classification Revisited: Automatic Content Analysis of Political Manifestos Using Active Learning." Social Science Computer Review 37, no. 2 (2018): 135–59. http://dx.doi.org/10.1177/0894439318758389.

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Supervised machine learning is a promising methodological innovation for content analysis (CA) to approach the challenge of ever-growing amounts of text in the digital era. Social scientists have pointed to accurate measurement of category proportions and trends in large collections as their primary goal. Proportional classification, for example, allows for time-series analysis of diachronic data sets or correlation of categories with text-external covariates. We evaluate the performance of two common approaches for this goal: a method based on regression analysis with feature profiles from en

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Kaushik, Divyansh, Zachary C. Lipton, and Alex John London. "Resolving the Human-subjects Status of Machine Learning's Crowdworkers." Queue 21, no. 6 (2023): 101–27. http://dx.doi.org/10.1145/3639452.

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In recent years, machine learning (ML) has relied heavily on crowdworkers both for building datasets and for addressing research questions requiring human interaction or judgment. The diversity of both the tasks performed and the uses of the resulting data render it difficult to determine when crowdworkers are best thought of as workers versus human subjects. These difficulties are compounded by conflicting policies, with some institutions and researchers regarding all ML crowdworkers as human subjects and others holding that they rarely constitute human subjects. Notably few ML papers involvi

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Mirri, Silvia, Catia Prandi, Paola Salomoni, Franco Callegati, Andrea Melis, and Marco Prandini. "A Service-Oriented Approach to Crowdsensing for Accessible Smart Mobility Scenarios." Mobile Information Systems 2016 (2016): 1–14. http://dx.doi.org/10.1155/2016/2821680.

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This work presents an architecture to help designing and deploying smart mobility applications. The proposed solution builds on the experience already matured by the authors in different fields: crowdsourcing and sensing done by users to gather data related to urban barriers and facilities, computation of personalized paths for users with special needs, and integration of open data provided by bus companies to identify the actual accessibility features and estimate the real arrival time of vehicles at stops. In terms of functionality, the first “monolithic” prototype fulfilled the goal of comp

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Christoforaki, Maria, and Oya Deniz Beyan. "Towards an ELSA Curriculum for Data Scientists." AI 5, no. 2 (2024): 504–15. http://dx.doi.org/10.3390/ai5020025.

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The use of artificial intelligence (AI) applications in a growing number of domains in recent years has put into focus the ethical, legal, and societal aspects (ELSA) of these technologies and the relevant challenges they pose. In this paper, we propose an ELSA curriculum for data scientists aiming to raise awareness about ELSA challenges in their work, provide them with a common language with the relevant domain experts in order to cooperate to find appropriate solutions, and finally, incorporate ELSA in the data science workflow. ELSA should not be seen as an impediment or a superfluous arte

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Kotliar, Michael, Andrey V. Kartashov, and Artem Barski. "CWL-Airflow: a lightweight pipeline manager supporting Common Workflow Language." GigaScience 8, no. 7 (2019). http://dx.doi.org/10.1093/gigascience/giz084.

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Abstract Background Massive growth in the amount of research data and computational analysis has led to increased use of pipeline managers in biomedical computational research. However, each of the >100 such managers uses its own way to describe pipelines, leading to difficulty porting workflows to different environments and therefore poor reproducibility of computational studies. For this reason, the Common Workflow Language (CWL) was recently introduced as a specification for platform-independent workflow description, and work began to transition existing pipelines and workflow managers t

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