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Machine Learning

Novel approach to refining risk stratification for colorectal cancer patients: application of deep convolutional neural networks (DCNN) to predict outcome and molecular subtyping
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Applicant:
Thiran, Jean-Philippe (EPFL)
Type:
iDoc Project
Categories:
Machine Learning, Oncology, Personalized diagnostics/treatment
Description:
DETAILS
Towards a new personalized in-vivo MRI biomarker of myelin integrity and damage in MS patients
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Applicant:
Fischi-Gomez, Elda | EPFL (Jean-Philippe Thiran)
Type:
Transition Postdoc Fellowship Project
Categories:
Big Data, Machine Learning, Personalized diagnostics/treatment
Description:
DETAILS
SHFN: SWISSHEART Failure Network (jointly with PHRT)
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Applicant:
Christian Matter (SPHN) & Joachim Buhmann (PHRT)
Type:
Driver Project
Categories:
Machine Learning, Platform
Description:

Heart failure (HF) is a frequently occurring syndrome whose multiple triggers and drivers remain poorly understood. Currently,…

DETAILS
Personalized Health: Building the relevant nutrition databases and APIs on openfood.ch
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Applicant:
Marcel Salathé (EPFL)
Type:
Seed Money Project
Categories:
Machine Learning
Description:

Building the open platform www.openfood.ch with the goal to contain nutritional information on all barcoded food products…

DETAILS
Santé personnalisée ? Oui, mais privée !
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Applicant:
Kévin Huguenin, Mathias Humbert, Michael Schumacher, Murielle Bochud
Type:
Recherche et dialogue interdisciplinaires dans le domaine de la santé personnalisée
Categories:
Machine Learning, Patient, Social/legal/ethics
Description:

La collecte et le stockage de données de natures très diverses – ainsi que leur partage entre spécialistes…

DETAILS
HMP: The Human Measurement Project Acronym Project
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Applicant:
Klaus Schönenberger, Robert West, Jean-Philippe Thiran, Matthias Roth-Kleiner, Thierry Agagliate
Type:
Module A
Categories:
Machine Learning, Patient
Description:

The overall goal of this project is to develop methods and tools based on image processing and…

DETAILS
iLearn: Interpretable Learning Methods for Immunotherapy
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Applicant:
Pascal Frossart (EPFL), Olivier Michielin (CHUV)
Type:
Module A
Categories:
Machine Learning, Oncology, Personalized diagnostics/treatment
Description:

The objective of this project is to develop a new data science framework built on novel neural network…

DETAILS
crowdAI: an open data science challenge platform integrating with the SDSC
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Applicant:
Marcel Salathé (EPFL)
Type:
Module B
Categories:
Machine Learning, Platform
Description:

The objective of this project is integrating crowdAI (open platform for data science challenges) with the SDSC…

DETAILS
Personalized Swiss Sepsis Study: Detection and modelling of sepsis using machine learning to analyse continuous ICU monitoring, laboratory, microbiology, and -omics data for personalized sepsis management (PSSS)
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Applicant:
Adrian Egli (USB, UniBS)
Type:
Driver Project, jointly with SPHN
Categories:
Big Data, Machine Learning, Personalized diagnostics/treatment
Description:

Within this collaborative network of all Swiss University Hospitals, Universities and ETH Zürich, we will generate a…

DETAILS
Personalized Swiss Sepsis Study: Detection and modelling of sepsis using machine learning to analyse continuous ICU monitoring, laboratory, microbiology, and -omics data for personalized sepsis management (PSSS)
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Applicant:
Adrian Egli (USB, UniBS)
Type:
Driver Project, jointly with PHRT
Categories:
Big Data, Machine Learning, Personalized diagnostics/treatment
Description:

Within this collaborative network of all Swiss University Hospitals, Universities and ETH Zürich, we will generate a…

DETAILS