RT @MCR_AACR: #AACR22 session primer, Building Tools for #MachineLearning and #ArtificialIntelligence in #CancerResearch: Best Practices &…

RT @MCR_AACR: #AACR22 session primer, Building Tools for #MachineLearning and #ArtificialIntelligence in #CancerResearch: Best Practices &…

#AACR22 session primer, Building Tools for #MachineLearning and #ArtificialIntelligence in #CancerResearch: Best Practices & Case Study with the #PathML Toolkit for #ComputationalPathology. https://t.co/qtsBxpBwM2 @MassimoLodaMD https://t.co/lOSLKiCkU

@fayyazhere PathML perspective ⭐ https://t.co/y7UPaI4Zcg ⭐ is described in this paper https://t.co/I2RCoujMyz - happy reading and let us know your comments or questions at [email protected]">@dfci.harvard.edu">[email protected] !

RT @renato_umeton: @muller_cardio I couldn't agree more!!! Have you seen this open source library? Designed by pathologists, implemented by…

RT @renato_umeton: @muller_cardio I couldn't agree more!!! Have you seen this open source library? Designed by pathologists, implemented by…

@muller_cardio I couldn't agree more!!! Have you seen this open source library? Designed by pathologists, implemented by data scientists and software engineers... Let us know your feedback! https://t.co/y7UPaI4rmI . Accompanying perspective paper at https:

RT @MCR_AACR: #ComputationalResearchers need tools such as #MachineLearning and #ArtificialIntelligence. Rosenthal et al discuss 3 themes t…

#ComputationalResearchers need tools such as #MachineLearning and #ArtificialIntelligence. Rosenthal et al discuss 3 themes to guide development of such tools: scalability, standardization and ease of use. https://t.co/NWsCHwPdYo @EcstaticIndian @TamikoV

RT @_JacobRosenthal: PathML, the software toolkit we've developed internally over the last 2.5yrs to power our computational pathology effo…

RT @_JacobRosenthal: PathML, the software toolkit we've developed internally over the last 2.5yrs to power our computational pathology effo…

RT @_JacobRosenthal: PathML, the software toolkit we've developed internally over the last 2.5yrs to power our computational pathology effo…

RT @_JacobRosenthal: PathML, the software toolkit we've developed internally over the last 2.5yrs to power our computational pathology effo…

PathML, the software toolkit we've developed internally over the last 2.5yrs to power our computational pathology efforts at @DanaFarber and @WCMCPathology, is now available publicly as open source: Github: https://t.co/Gzn9Y86vPl Paper: https://t.co/sCoz

Building tools for machine learning and artificial intelligence in cancer research: best practices and a case study with the PathML toolkit for computational pathology https://t.co/XnUeTxcDas