Resolving phenotyping discordance with SPACEMAP, an integrated machine learning framework.
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| Title: | Resolving phenotyping discordance with SPACEMAP, an integrated machine learning framework. |
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| Authors: | Dawod B; Department of Radiation Oncology, the University of Southwestern Medical Center, Dallas, TX, USA., Rodriguez AP; Department of Radiation Oncology, the University of Southwestern Medical Center, Dallas, TX, USA., Diegeler S; Department of Radiation Oncology, the University of Southwestern Medical Center, Dallas, TX, USA.; Current address: Department of Pathology, University of Cambridge, Cambridge, UK., Elghonaimy E; Department of Radiation Oncology, the University of Southwestern Medical Center, Dallas, TX, USA., Wachsman M; Department of Pathology, the University of Texas Southwestern Medical Center, Dallas, TX, USA.; Pathology and Laboratory Medicine Services, Veterans Affairs North Texas Health Care System, Dallas, TX, USA., Gopal P; Department of Pathology, the University of Texas Southwestern Medical Center, Dallas, TX, USA.; Pathology and Laboratory Medicine Services, Veterans Affairs North Texas Health Care System, Dallas, TX, USA., Hein D; Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA., Acosta PH; Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA., Jamieson A; Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA., Danuser G; Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA., Timmerman RD; Department of Radiation Oncology, the University of Southwestern Medical Center, Dallas, TX, USA., Rajaram S; Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA., Aguilera TA; Department of Radiation Oncology, the University of Southwestern Medical Center, Dallas, TX, USA. |
| Source: | BioRxiv : the preprint server for biology [bioRxiv] 2025 Dec 01. Date of Electronic Publication: 2025 Dec 01. |
| Publication Type: | Journal Article; Preprint |
| Journal Info: | Country of Publication: United States NLM ID: 101680187 Publication Model: Electronic Cited Medium: Internet ISSN: 2692-8205 (Electronic) Linking ISSN: 26928205 NLM ISO Abbreviation: bioRxiv Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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