Machine Learning in Biomedicine group
@mlbiomed
MLBioMed group at @FIMM_UH / @HiLIFE_helsinki / @helsinkiuni. Affiliated with @ATGprogram and @ican_finland. PI @epitkane
ID: 1191412573171781632
https://www.helsinki.fi/en/researchgroups/machine-learning-in-biomedicine 04-11-2019 17:51:49
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Thank you for your support! FIMM HelsinkiUni @amchelsinki University of Helsinki Esa Pitkänen
Machine Learning in Biomedicine group and Waara lab are looking for a postdoc to join our iCAN - Digital Precision Cancer Medicine funded project on hematological single-cell genomics! FIMM HelsinkiUni helsinki.fi/en/open-positi…
New paper out! Joona Pohjonen showed that spectral decoupling (=L2 penalty on prediction logits) can improve accuracy of medical imaging models in independent datasets up to ~10 pp. Great collab with Tuomas Mirtti Antti Rannikko sciencedirect.com/science/articl…
Excited to announce our new manuscript on tumor (sub)typing in NGS data! Wonderful work by Prima Sanjaya in collab with Sebastian Waszak Oliver Stegle Jan Korbel FIMM HelsinkiUni Applied Tumor Genomics (ATG) Machine Learning in Biomedicine group biorxiv.org/content/10.110…
How to virtually label cells with imaging flow cytometry (IFC) and identify cell types? Veera Timonen created DeepIFC to solve this problem. Great collaboration with Finnish Red Cross Blood Service Veripalvelu FIMM HelsinkiUni Applied Tumor Genomics (ATG) University of Helsinki Machine Learning in Biomedicine group biorxiv.org/content/10.110…
Happy to see our paper on reconstructing fluorescent labels in imaging flow cytometry with deep learning published. Excellent work by Veera Timonen and collaborators! FRCBSresearch Machine Learning in Biomedicine group FIMM HelsinkiUni onlinelibrary.wiley.com/doi/abs/10.100…
Wonderful to see our work on (deep) learning how to classify tumor types with WGS/WES data published in Genome Medicine! Great effort by Prima Sanjaya and coauthors to validate the method in >10,000 whole cancer genomes. FIMM HelsinkiUni Applied Tumor Genomics (ATG) iCAN - Digital Precision Cancer Medicine genomemedicine.biomedcentral.com/articles/10.11…
MuAt presented by Prima Sanjaya Esa Pitkänen &co FIMM HelsinkiUni Applied Tumor Genomics (ATG) iCAN - Digital Precision Cancer Medicine is a deep neural network to learn representations of simple & complex somatic alterations for prediction of tumour types, with potential to impact precision #cancer medicine bit.ly/44vxhrA
