Patient-by-Patient Deep Transfer Learning for Drug-Response Profiling Using Confocal Fluorescence Microscopy of Pediatric Patient-Derived Tumor-Cell Spheroids

Author:

Berker Yannick1ORCID,ElHarouni Dina1ORCID,Peterziel Heike2,Fiesel Petra1,Witt Olaf1,Oehme Ina2ORCID,Schlesner Matthias3ORCID,Oppermann Sina2ORCID

Affiliation:

1. Hopp Children’s Cancer Center Heidelberg (KiTZ), Heidelberg, Germany

2. German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Clinical Cooperation Unit Pediatric Oncology, Heidelberg, Germany

3. German Cancer Research Center (DKFZ), Bioinformatics and Omics Data Analytics, Heidelberg, Germany

Funder

Federal Ministry of Education and Research (BMBF) under the frame of ERA PerMed

KirstinsWeg – Verein zur Förderung der Krebsmedizin e.V. and the Kirstin Diehl-Stiftung

German Cancer Consortium (DKTK), BMBF, and the Scheu Family

Deutsche Krebshilfe

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Radiological and Ultrasound Technology,Software

Reference70 articles.

1. MobileNets: Efficient convolutional neural networks for mobile vision applications;howard;arXiv 1704 04861,2017

2. ImageNet: A large-scale hierarchical image database

3. Very deep convolutional networks for large-scale image recognition;simonyan;Proc 3rd Int Conf Learn Represent (ICLR),2015

4. Abstract A40: Integration of high-throughput drug screening on patient-derived organdies into pediatric precision medicine programs: The future is now!

5. The Pediatric Precision Oncology INFORM Registry: Clinical Outcome and Benefit for Patients with Very High-Evidence Targets

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