Zobrazeno 1 - 10
of 213
pro vyhledávání: '"Heinrich Roder"'
Autor:
Matthew A. Koc, Timothy Aaron Wiles, Daniel C. Weinhold, Steven Rightmyer, Amanda L. Weaver, Colin T. McDowell, Joanna Roder, Senait Asmellash, Gary A. Pestano, Heinrich Roder, Robert W. Georgantas III
Publikováno v:
Journal of Mass Spectrometry and Advances in the Clinical Lab, Vol 30, Iss , Pp 51-60 (2023)
Introduction: The VeriStrat® test (VS) is a blood-based assay that predicts a patient's response to therapy by analyzing eight features in a spectrum obtained from matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) analysis of hu
Externí odkaz:
https://doaj.org/article/479f48e24ad04e988a1048bcc0e97435
Autor:
Alessandra I. G. Buma, Berber Piet, Rob ter Heine, Michel M. van den Heuvel, Paul Brinkman, Daan van den Broek, Sjaak Burgers, Francesco Ciompi, Simona M. Cristescu, Bram van Ginneken, Katrien Grünberg, Lizza Hendriks, Jeroen Hiltermann, Firdaus Mohamed Housein, Alwin Huitema, Jakko van Inge, Colin Jacobs, Hans Koenen, Marjolijn Ligtenberg, Anke H. Maitland-van der Zee, Vincent van der Noort, Mathias Prokop, Valesca Rètel, Heinrich Roder, Huub van Rossum, Ruben Smeets, Thomas Würdinger
Publikováno v:
Frontiers in Pharmacology, Vol 14 (2023)
Personalization of treatment offers the opportunity to treat patients more effectively based on their dominant disease-specific features. The increasing number and types of treatment, and the high costs associated with these treatments, however, dema
Externí odkaz:
https://doaj.org/article/625220bc2e1044659b79873cb9c7aed9
Publikováno v:
Machine Learning with Applications, Vol 9, Iss , Pp 100345- (2022)
Additive feature explanations using Shapley values have become popular for providing transparency into the relative importance of each feature to an individual prediction of a machine learning model. While Shapley values provide a unique additive fea
Externí odkaz:
https://doaj.org/article/9f451140d85f4cbf89122fa0a5d72f66
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 21, Iss 1, Pp 1-18 (2021)
Abstract Background Machine learning (ML) can be an effective tool to extract information from attribute-rich molecular datasets for the generation of molecular diagnostic tests. However, the way in which the resulting scores or classifications are p
Externí odkaz:
https://doaj.org/article/4f0c66e78c2a4bc59546bba35c72c901
Autor:
Joanna Roder, Heinrich Roder, Senait Asmellash, Minu Srivastava, Wei Zou, Mark McCleland, David Shames, Laura Maguire, Steven Rightmyer, Patrick Norman, Lelia Net, Thomas Campbell, Robert Georgantas
Publikováno v:
Journal for ImmunoTherapy of Cancer, Vol 9, Iss Suppl 2 (2021)
Externí odkaz:
https://doaj.org/article/53f8edef70ba49fcb857563e894b33bc
Autor:
Joanna Roder, Heinrich Roder, Senait Asmellash, Minu Srivastava, Wei Zou, Mark McCleland, David Shames, Laura Maguire, Steven Rightmyer, Patrick Norman, Lelia Net, Thomas Campbell, Robert Georgantas
Publikováno v:
Journal for ImmunoTherapy of Cancer, Vol 9, Iss Suppl 2 (2021)
Externí odkaz:
https://doaj.org/article/8bda803207af4c5aabd84706f05249c0
Autor:
Joanna Roder, Heinrich Roder, Minu Srivastava, Wei Zou, Mark McCleland, David Shames, Laura Maguire, Lelia Net, Thomas Campbell, Robert Georgantas
Publikováno v:
Journal for ImmunoTherapy of Cancer, Vol 9, Iss Suppl 2 (2021)
Externí odkaz:
https://doaj.org/article/7395001df9114371ba0212201b1f030a
Autor:
Takuya Mizukami, Heinrich Roder
Publikováno v:
Molecules, Vol 27, Iss 11, p 3392 (2022)
Many important biological processes such as protein folding and ligand binding are too fast to be fully resolved using conventional stopped-flow techniques. Although advances in mixer design and detection methods have provided access to the microseco
Externí odkaz:
https://doaj.org/article/249af164c4924b8b98e45b41af34a252
Publikováno v:
BMC Bioinformatics, Vol 20, Iss 1, Pp 1-14 (2019)
Abstract Background Modern genomic and proteomic profiling methods produce large amounts of data from tissue and blood-based samples that are of potential utility for improving patient care. However, the design of precision medicine tests for unmet c
Externí odkaz:
https://doaj.org/article/cc3d328383f249f9a91a40d28afe7e81
Publikováno v:
BMC Bioinformatics, Vol 20, Iss 1, Pp 1-25 (2019)
Abstract Background Modern molecular profiling techniques are yielding vast amounts of data from patient samples that could be utilized with machine learning methods to provide important biological insights and improvements in patient outcomes. Unsup
Externí odkaz:
https://doaj.org/article/212178dfa247411b8864f81c70ed1d7c