Machine Learning and the Life Sciences

DESCRIPTION

Artificial Intelligence has become pivotal for research and innovation in health care. An increasing number of algorithms find their way to clinical practice providing powerful solutions and assisting medical doctors in their everyday practice. We study deep-learning-based approaches in this domain and work towards novel, unbiased, and generalizable algorithms for cancer treatment and response to immunotherapy. Of particular interest are learning schemes for training on gigapixel histopathological slides, transformer-based architectures with different attention schemes for the fusion of histopathology and genetic/clinical information, and bias identification and domain adaptation methods based on the image-to-image translation and adversarial attacks for addressing domain shifts and possibly biological and clinical biases.

RESEARCHERS

archontis-giannakidis
Archontis Giannakidis
Nottingham Trent University
giorgos-papanastasiou
Giorgos Papanastasiou
University of Essex
maria-papadopouli
Maria Papadopouli
University of Crete & Foundation for Research and Technology-Hellas (FORTH)
maria-vakalopoulou
Maria Vakalopoulou
Centrale Supélec, University Paris-Saclay
polydoros-kampaktsis
Polydoros Kampaktsis
Aristotle University of Thessaloniki
sotirios-tsaftaris
Sotirios Tsaftaris
THE UNIVERSITY OF EDINBURGH
 
 

The project “ARCHIMEDES Unit: Research in Artificial Intelligence, Data Science and Algorithms” with code OPS 5154714 is implemented by the National Recovery and Resilience Plan “Greece 2.0” and is funded by the European Union – NextGenerationEU.

greece2.0 eu_arch_logo_en

 

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