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Computational flow cytometry as a diagnostic tool in suspected‐myelodysplastic syndromes

Carolien Duetz, Sofie Van Gassen, Theresia M. Westers, Margot F. van Spronsen, Costa Bachas, Yvan Saeys, Arjan A. van de Loosdrecht
2021 Cytometry Part A  
For practical advantages (e.g. reduced processing time and costs), a second computational diagnostic workflow was trained, solely based on the best performing single tube of the training cohort.  ...  Both workflows outperformed the conventional, expert analyzed flow cytometry scores for diagnosis with respect to accuracy, objectivity and time investment (less than three minutes per patient).  ...  ACKNOWLEDGMENTS We would like to thank all technicians for collecting and analyzing the  ... 
doi:10.1002/cyto.a.24360 pmid:33942494 fatcat:62vq5d7iwfgjveo2wm4cbvp2oq


M. Maciukiewicz, J. Schniering, H. Gabrys, M. Brunner, C. Blüthgen, C. Meier, M. Guckenberger, H. Fretheim, A. M. Hoffmann-Vold, O. Distler, T. Frauenfelder, S. Tanadini-Lang (+1 others)
2021 Annals of the Rheumatic Diseases  
Resolving phenotypic and prognostic differences in interstitial lung disease related to systemic sclerosis by computed tomography-based radiomics.  ...  As we perform feature selection in 5k CV workflow, features present in at least 2 sets entered model optimization step.During model selection, we selected RF classifier.  ...  We have developed a systematic computational workflow to build predictive ML models. To reduce the number of redundant radiomic features, we applied correlation thresholds.  ... 
doi:10.1136/annrheumdis-2021-eular.2517 fatcat:hreot2hb7zdfxnjanzkqlnn4aq

WOWMON: A Machine Learning-based Profiler for Self-adaptive Instrumentation of Scientific Workflows

Xuechen Zhang, Hasan Abbasi, Kevin Huck, Allen D. Malony
2016 Procedia Computer Science  
performance data based on local information from coupled scientific applications of workflows, particularly at runtime. 2) Profiling/tracing with static instrumentation may incur high overhead and significantly  ...  Performance debugging using program profiling and tracing for scientific workflows can be extremely difficult for two reasons. 1) Existing performance tools lack the ability to automatically produce global  ...  We thank Jai Dayal and Matthew Wolf for their support on the LAMMPS workflow instrumentation. We also thank Wyatt Spear for many discussions during this work.  ... 
doi:10.1016/j.procs.2016.05.474 fatcat:jr7uyavgcfelncbfwnkz5n66ma

Artificial Intelligence in Digital Breast Pathology: Techniques and Applications

Asmaa Ibrahim, Paul Gamble, Ronnachai Jaroensri, Mohammed M. Abdelsamea, Craig H. Mermel, Po-Hsuan Cameron Chen, Emad A. Rakha
2019 Breast  
In parallel, advances in artificial intelligence (AI) along with the growing digitization of pathology slides for the primary diagnosis are a promising approach to meet the demand for more accurate detection  ...  The mainstay of breast cancer workup is histopathological diagnosis - which guides therapy and prognosis.  ...  In 2016, the Granada University Hospital system adopted an entirely digital workflow for primary histopathology diagnosis.  ... 
doi:10.1016/j.breast.2019.12.007 pmid:31935669 pmcid:PMC7375550 fatcat:u24dfeb6zndvpcsx56cgkhcifm

Practical Strategies for Extreme Missing Data Imputation in Dementia Diagnosis

Niamh Mccombe, Shuo Liu, Xuemei Ding, Girijesh Prasad, Magda Bucholc, David Finn, Stephen Todd, Paula L Mcclean, Kongfatt Wong-Lin
2021 IEEE journal of biomedical and health informatics  
Accurate computational models for clinical decision support systems require clean and reliable data but, in clinical practice, data are often incomplete.  ...  In particular, we focus on dementia diagnosis due to long time delays, high variability, high attrition rates and lack of practical data imputation strategies in its diagnostic pathway.  ...  Features included 7 different Cognitive and Functional Assessment (CFA) scores as well as Gender, Age and text-based Diagnosis information.  ... 
doi:10.1109/jbhi.2021.3098511 pmid:34288882 fatcat:zvunfjlcqfcibk3256ocng7coa

Computational biomedicine: The role of workflow tools

S.J. Zasada, P.V. Coveney
2010 Procedia Computer Science  
Distributed and high performance computing are increasingly finding a role in medical research and ultimately simulation using high performance and distributed computing is likely to be used to support  ...  In this paper we analyse the needs of computational biomedicine projects to uncover the key, generic requirements they have from a workflow system.  ...  . 5. the workflow system should be able to execute applications on batch computing systems. 6. the workflow system should support a high level of security.  ... 
doi:10.1016/j.procs.2010.04.309 fatcat:d55t4mw5trfsthsknlgoqu2esi

Radiomics and Texture Analysis in Laryngeal Cancer. Looking for New Frontiers in Precision Medicine through Imaging Analysis

Chiesa-Estomba, Echaniz, Larruscain, Gonzalez-Garcia, Sistiaga-Suarez, Graña
2019 Cancers  
We hypothesized that radiomics features can be included as a laryngeal cancer precision medicine tool, as it is able to non-invasively characterize the overall tumor accounting for heterogeneity, being  ...  These techniques extract a large number of quantitative features, analyzing their properties to incorporate them in clinical decision-making.  ...  The most common image features are those based simply on voxel intensity values within a region of interest (ROI).  ... 
doi:10.3390/cancers11101409 pmid:31547210 pmcid:PMC6826870 fatcat:quh56irzzvhhnfmsi7ylva463a

Responsible Radiomics Research for Faster Clinical Translation

Martin Vallières, Alex Zwanenburg, Bodgan Badic, Catherine Cheze Le Rest, Dimitris Visvikis, Mathieu Hatt
2017 Journal of Nuclear Medicine  
Computer-aided diagnosis methods and systems exploiting medical images have been developed for decades, but their wide clinical implementation has been hampered by false-positive rates (3) .  ...  Other major issues include the limited number of patients available for radiomics research, high false-positive rates (similarly to analogous computer-aided diagnosis methods) and the reporting of over-optimistic  ... 
doi:10.2967/jnumed.117.200501 pmid:29175982 pmcid:PMC5807530 fatcat:jm5qijrrhrdjbdzmdyrdf7zok4

Practical strategies for large missing data in dementia diagnosis [article]

Niamh McCombe, Shuo Liu, Xuemei Ding, Girijesh Prasad, Magda Bucholc, David P Finn, Stephen Todd, Paula L McClean, KongFatt Wong-Lin
2020 medRxiv   pre-print
This work addresses the problem by evaluating multiple imputation and classification workflows based not only on diagnostic classification accuracy but also computational cost.  ...  Accurate computational models for clinical decision support systems require clean and reliable data, but in clinical practice, data are often incomplete.  ...  Based on text-based diagnosis from clinicians, AD diagnosis was manually categorized into two classes, AD MILD (mild AD) and AD MOD (moderate AD).  ... 
doi:10.1101/2020.07.13.20146118 fatcat:um4mmasaubdxlg2u3toqs5sbaq

Current and future applications of artificial intelligence in pathology: a clinical perspective

Emad A Rakha, Michael Toss, Sho Shiino, Paul Gamble, Ronnachai Jaroensri, Craig Mermel, Cameron Chen
2020 Journal of Clinical Pathology  
We examine its applications in diagnosis and prognosis, and we offer insights for considerations that could improve clinical applicability of these tools.  ...  Then, we discuss its potential to improve workflow efficiency, and its benefits in pathologist education.  ...  Acknowledgements We would like to thank Dr Henry Ebili for his kind contribution to this review.  ... 
doi:10.1136/jclinpath-2020-206908 pmid:32763920 fatcat:h2n4wlqzojdfnnzrfeylohuuli

DIADS: Addressing the "My-Problem-or-Yours" Syndrome with Integrated SAN and Database Diagnosis

Shivnath Babu, Nedyalko Borisov, Sandeep Uttamchandani, Ramani Routray, Aameek Singh
2009 USENIX Conference on File and Storage Technologies  
We present DIADS, an integrated DIAgnosis tool for Databases and Storage area networks (SANs). Existing diagnosis tools in this domain have a database-only (e.g., [11] ) or [28] ) focus.  ...  The machine learning component provides core techniques for problem diagnosis from monitoring data, and domain knowledge acts as checks-andbalances to guide the diagnosis in the right direction.  ...  Diagnosis Workflow: DIADS then invokes the workflow shown in Figure 3 to diagnose the query slowdown based on the monitoring data collected for satisfactory and unsatisfactory runs.  ... 
dblp:conf/fast/BabuBURS09 fatcat:ey4qpxgynfbrve4kdabskzv2qm

Metabolomics-Based Screening of Inborn Errors of Metabolism: Enhancing Clinical Application with a Robust Computational Pipeline

Brechtje Hoegen, Alan Zammit, Albert Gerritsen, Udo F H Engelke, Steven Castelein, Maartje van de Vorst, Leo A J Kluijtmans, Marleen C D G Huigen, Ron A Wevers, Alain J van Gool, Christian Gilissen, Karlien L M Coene (+1 others)
2021 Metabolites  
The pipeline implements a combination of tools embedded in a workflow environment for large-scale clinical metabolomics data analysis.  ...  We have previously established next-generation metabolic screening (NGMS) as a metabolomics-based diagnostic tool for analyzing plasma of individual IEM-suspected patients.  ...  Acknowledgments: We are indebted to Siebolt de Boer, Joris Reintjes and Ed van der Heeft for technical assistance in metabolomics measurements.  ... 
doi:10.3390/metabo11090568 pmid:34564390 pmcid:PMC8470724 fatcat:73twlfpiwzhpvnycuqjyqy26pq

Application of Radiomics and Decision Support Systems for Breast MR Differential Diagnosis

Ioannis Tsougos, Alexandros Vamvakas, Constantin Kappas, Ioannis Fezoulidis, Katerina Vassiou
2018 Computational and Mathematical Methods in Medicine  
Over the years, MR systems have evolved from imaging modalities to advanced computational systems producing a variety of numerical parameters that can be used for the noninvasive preoperative assessment  ...  The scope of this review is to provide applications and limitations of radiomics towards the development of clinical decision support systems for breast cancer diagnosis and prognosis.  ...  .), in the radiomic analysis workflow towards lesion evaluation for diagnosis and Computational and Mathematical Methods in Medicine selection of appropriate treatment plan. e precise definition of breast  ... 
doi:10.1155/2018/7417126 fatcat:z25pzfuwnzfthdf762nchgcphy

Radiomics: from qualitative to quantitative imaging

William Rogers, Sithin Thulasi Seetha, Turkey A. G. Refaee, Relinde I. Y. Lieverse, Renée W. Y. Granzier, Abdalla Ibrahim, Simon A. Keek, Sebastian Sanduleanu, Sergey P. Primakov, Manon P. L. Beuque, Damiënne Marcus, Alexander M. A. van der Wiel (+5 others)
2020 British Journal of Radiology  
Handcrafted radiomics is a multistage process in which features based on shape, pixel intensities, and texture are extracted from radiographs.  ...  As a result of advances in both computational hardware and machine learning algorithms, computers are making great strides in obtaining quantitative information from imaging and correlating it with outcomes  ...  on computerised quantitative analysis of medical data for aiding clinical diagnosis, [7] [8] [9] what later came to be known as computer-aided diagnosis (CAD) systems.  ... 
doi:10.1259/bjr.20190948 pmid:32101448 fatcat:mnhaur7dyrhanio63v6kdbdthm

Integrating pathology and radiology disciplines: an emerging opportunity?

James Sorace, Denise R Aberle, Dena Elimam, Silvana Lawvere, Ossama Tawfik, W Dean Wallace
2012 BMC Medicine  
In addition, lesion characterizations by high-resolution helical computed tomography have introduced a new classification of peripheral lung lesions, such as ground-glass and part-solid nodules, that correlate  ...  both humans and computers, to facilitate data mining and querying of reports, to automate image annotation and computer-aided diagnosis, and to enable teaching files and decision support [24, 25] .  ... 
doi:10.1186/1741-7015-10-100 pmid:22950414 pmcid:PMC3523019 fatcat:q2bwex4mbvbjbilvz765kywn54
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