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Machine Learning Frontiers in Precision Medicine

Deliverables

Software implementing the method developed

ESR 9: Software implementing the method developed

1st summer school

1st summer school

Systematic review on existing methods

ESR 9: Systematic review on existing methods

2nd summer school

2nd summer school

Methodology to embed sparse somatic genetic profiles

ESR 5: Methodology to embed sparse somatic genetic profiles

Comparison of methods for network analysis of individual omics data

ESR 12: Comparison of methods for network analysis of individual comics data

Publication describing the application of current causal inference tools to a representative use-case

ESR 14: Publication describing the application of current causal inference tools to a representative use-case

Deep learning methods to find molecular components relevant for signaling that define functions that can be related to phenotypes (disease, drug response, etc.)

ESR 9: Deep learning methods to find molecular components relevant for signaling that define functions that can be related to phenotypes (disease, drug response, etc.)

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Publications

Biological network analysis with deep learning

Author(s): Giulia Muzio, Leslie O’Bray, Karsten Borgwardt
Published in: Briefings in Bioinformatics, 2020, ISSN 1467-5463
DOI: 10.1093/bib/bbaa257

AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID-19

Author(s): Parthasarathy Suryanarayanan, Ching-Huei Tsou, Ananya Poddar, Diwakar Mahajan, Bharath Dandala, Piyush Madan, Anshul Agrawal, Charles Wachira, Osebe Mogaka Samuel, Osnat Bar-Shira, Clifton Kipchirchir, Sharon Okwako, William Ogallo, Fred Otieno, Timothy Nyota, Fiona Matu, Vesna Resende Barros, Daniel Shats, Oren Kagan, Sekou Remy, Oliver Bent, Pooja Guhan, Shilpa Mahatma, Aisha Walcott-Bryant, Div
Published in: Scientific Data, Issue 8/1, 2021, ISSN 2052-4463
DOI: 10.1038/s41597-021-00878-y

Shift in Social Media App Usage During COVID-19 Lockdown and Clinical Anxiety Symptoms: Machine Learning–Based Ecological Momentary Assessment Study

Author(s): Jihan Ryu, Emese Sükei, Agnes Norbury, Shelley H Liu, Juan José Campaña-Montes, Enrique Baca-Garcia, Antonio Artés, M Mercedes Perez-Rodriguez
Published in: JMIR Mental Health, Issue 8/9, 2021, Page(s) e30833, ISSN 2368-7959
DOI: 10.2196/30833

Predicting Emotional States Using Behavioral Markers Derived From Passively Sensed Data: Data-Driven Machine Learning Approach

Author(s): Emese Sükei, Agnes Norbury, M Mercedes Perez-Rodriguez, Pablo M Olmos, Antonio Artés
Published in: JMIR mHealth and uHealth, Issue 9/3, 2021, Page(s) e24465, ISSN 2291-5222
DOI: 10.2196/24465

Network Aggregation to Enhance Results Derived from Multiple Analytics

Author(s): Diane Duroux, Héctor Climente-González, Lars Wienbrandt, Kristel Van Steen
Published in: Artificial Intelligence Applications and Innovations - 16th IFIP WG 12.5 International Conference, AIAI 2020, Neos Marmaras, Greece, June 5–7, 2020, Proceedings, Part I, Issue 583, 2020, Page(s) 128-140
DOI: 10.1007/978-3-030-49161-1_12