Rok 2023

• Neural Graph Collaborative Filtering: Analysis of Possibilities on Diverse Datasets

  Publikacja

  • D. Kobiela
  • J. Groth
  • M. Sieczczyński
  • R. Wolniak
  • K. Pastuszak

  - Rok 2023

  This paper continues the work by Wang et al. [17]. Its goal is to verify the robustness of the NGCF (Neural Graph Collaborative Filtering) technique by assessing its ability to generalize across different datasets. To achieve this, we first replicated the experiments conducted by Wang et al. [17] to ensure that their replication package is functional. We received sligthly better results for ndcg@20 and somewhat poorer results for...

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• Platelet RNA Sequencing Data Through the Lens of Machine Learning

  Publikacja

  • S. Cygert
  • K. Pastuszak
  • F. Górski
  • M. Sieczczyński
  • P. Juszczyk
  • A. Rutkowski
  • S. Lewalski
  • R. Różański
  • M. A. Jopek
  • J. Jassem... i 5 innych

  - Cancers - Rok 2023

  Liquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...

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