Atif Khan
@atifncl
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Postdoc in AI and biomedicine at @HRazaAliLab @Cambridge_Uni | Passionate and realistic about capability of AI | love family, tennis & cricket
Newcastle upon Tyne
Joined September 2017
Acknowledgement: This was only possible due to precious tissue donated by patients and healthy donors.
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(3/3) making this ready to build & train a fully automatic AI pipeline for SM analysis. This work was not possible without generous support from @ccbdcdt (& @epsrc @RedHat @MicrosoftUK ), colleagues at @MitoResearch @mitomusclelab and our labelling partner at Gamaed.
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(2/3) Full paper:(accepted in BDA4HM, IEEE BigData 2023). The NCL-SM consist of >50k high quality manually annotated skeletal muscle (SM) fibres/myofibres. Paving solid foundation to train AI models. We also classify non-analysable myofibres and regions.
arxiv.org
Single cell analysis of human skeletal muscle (SM) tissue cross-sections is a fundamental tool for understanding many neuromuscular disorders. For this analysis to be reliable and reproducible,...
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(1/3)We release the NCL-SM: A Fully Annotated Dataset of Images from Human Skeletal Muscle Biopsies. By I, @cnrlwlss , @AmyV91 ,@Charwarren25 , @ValDiLeoMito , @TiagoMBGomes & @stevemcgough.Short paper:-accepted in findings @SymposiumML4H-🙏 travel award
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RT @cnrlwlss: The first describes the process of writing a model in C++ and how to execute 35,328 independendent simulations from that mode….
jordanbchilds.github.io
Introduction In this article we will discuss how to execute a large number of independent programs in parallel, using a new computer chip capable of executing thousands of independent calculations at...
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RT @cnrlwlss: IPUs from @graphcoreai are highly parallelisable processors. Recently, Jordan Childs, one of my students at the WCMR (@Mit….
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