Insight Centre for Data Analytics at National University of Ireland, Graph Mining, Machine Learning , Datamining

Ireland
Joined May 2015
Delighted to be in the @GalwayIdeasLab this evening learning about artificial intelligence (AI) and teasing our the role Public and Patient Involvement can have to support this phenomena.
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Mohan Timilsina retweeted
Mathematics. A Universe of Linear Algebra. Welcome to Matrix World. Source: github.com/kenjihiranabe/The…
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I am delighted to share that our research in Chronic Kidney Disease got best abstract award in prestigious European Renal Association (61st ERA-20024) Congress in Stockholm, Sweden ☺️☺️😃. #ERA2024, @austingstack, @MedicineAtUL @UL_Research @UL, @ERAkidney
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I am thrilled to chair a session and present my work "Machine Learning Survival Models for Relapse Prediction in a Early Stage Lung Cancer Patient" at the International Joint Conference of Neural Networks (IJCNN 2023, Gold Coast, Australia )! @galwayDSI @insight_centre #IJCNN2023
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Our work on "Neural age screening on question answering communities" is now officially published in "Engineering Applications of Artificial Intelligence" [IF: 7.8]. @galwayDSI @insight_centre sciencedirect.com/science/ar…
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Our paper "Machine Learning Survival Models for Relapse Prediction in an Early Stage Lung Cancer Patient'" has been accepted in the International Joint Conference on Neural Networks (IJCNN) (2023.ijcnn.org/). In this work, we explored off-the-shelf survival models to
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predict the relapse of early-stage lung cancer patients. We analyzed the survival models on a cohort of early-stage non-small cell lung cancer(NSCLC) patients in different timestamps. Using the prediction explanation model SHAP (SHapley Additive exPlanations), we further
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explained the best-performing survival model’s predictions.
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Next for World Health Day is Dr Mohan Timilsina's work in Insight @uniofgalway, using #AI and data to drive better and more personalised #cancer care. Read about it here:insight-centre.org/world-hea… @Scienceirel @dcu @ucc @ucddublin
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Our work "Boundary heat diffusion classifier for a semi-supervised learning in a multilayer network embedding" is now published in Neural Networks [IF:9.657] sciencedirect.com/science/ar… @galwayDSI, @mdaquin,@insight_centre
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Our work predicting the onset time of the adverse drug events in oncology is published. Several traditional tabular, matrix factorisation, graph-based semi supervised and embedding machine learning models are tested in FAERS data.@MeeraTandan @DSIatNUIG sciencedirect.com/science/ar…
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Mohan Timilsina retweeted
XGBoost Is All You Need Deep Neural Networks and Tabular Data: A Survey arxiv.org/pdf/2110.01889.pdf
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Interpretable ML/XAI recent PhD graduate looking for openings? Say no more! Check out this 2y PostDoc opening with @adrian_weller, in partnership with @turinginst and Accenture Labs et al. Few days left to apply! cezanneondemand.intervieweb.…
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Virtually presented our work "On Predicting Recurrence in Early Stage Non-small Cell Lung Cancer" at #AMIA2021, @DSIatNUIG @Clarify2020
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Mohan Timilsina retweeted
The @Clarify2020 project is recruiting! Join @nuigalway as Research Associate to help us with interpretable ML for oncological treatment. Deadline: *Oct 29*! /cc @PMinervini @adri_janik @mohan_timilsina nuigalway.ie/media/humanreso…
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Our collaborative work to identify the different age cohorts in Yahoo! Answers is now published in Knowledge Based Systems (IF: 8.038) @DSIatNUIG sciencedirect.com/science/ar…
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Mohan Timilsina retweeted
3 fully funded #PhD positions on research with health data in the @hrbireland @CARAnetwork1 project led by @Dr_Akke. Training in the @sphereprogramme. See details at caranetwork.ie @drccostelloe @porwolluke @AjayOza_Actual @ResearchatNUIG @DSIatNUIG
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Docker for absolute beginners — what is Docker and how to use it (+ examples) by Mike Huls buff.ly/2TtRgYc
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GMM: Gaussian Mixture Models — How to Successfully Use It to Cluster Your Data? by @SolClover buff.ly/3ufq7oH
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Machine Learning Prediction in Real Time Using Docker and Python REST APIs with Flask by @VasquesXavier buff.ly/3t89Z7X
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