Call for Papers

We invite contributions from both industry and academia to share their research and experience in using artificial intelligence and machine learning methods in pharmaceutical research and development. PharML will be held at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) to take place in Ghent, Belgium, on 14th - 18th of September 2020.

Submission Guidelines

We invite authors to submit extended abstracts including preliminary results as well as published work. Authors should submit a paper of up to 4 pages (excluding references). Longer papers will be rejected immediately. Priority will be given to unpublished work. Authors should commit to present their work at the workshop in case it is accepted for an oral or poster presentation. All accepted abstracts will be posted on the workshop's website.

• The peer-review process is strictly double-blind.

• All submissions must be anonymous. Make sure the PDF file you upload does not contain names, affiliations, acknowledgements or any information that can be used to directly identify you. Replace the author information with "Anonymous". Avoid including URLs of GitHub repositories linked to you.

• Abstracts should be in PDF format, following the Springer Lecture Notes in Computer Science style

• Submissions should be done via the workshop EasyChair page
  

Topics of Interest

The following list, although not exhaustive, covers some of the main topics that will be discussed in the workshop.

• Learning on Graphs

  • Representing patients and molecules as graphs

  • Transfer learning and generative models

  • Modelling dynamic graphs

  • Node and link prediction on molecular graphs

  • Biological pathway mining for cancer biomarker discovery

  • Machine learning with brain graphs

  • Causal structure learning from real world data

• Deep learning in healthcare and pharmaceutical research

  • Medical Imaging

  • Natural Language Processing

  • Reinforcement learning in computer-assisted procedures

  • Audio Processing

  • Time series analysis

• Bayesian methods

  • Modelling uncertainty

  • Bayesian methods for classification and imputation

  • Bayesian networks

• General machine learning methods for healthcare and pharma

  • Machine learning for personalized healthcare

  • Multimodal machine learning (e.g. combining genomics, pathology reports, clinical data to predict survival)

  • Remote sensing for healthcare applications

  • Causal inference with observational data

  • Subgroup discovery and targeted learning

  • Longitudinal and trajectory data analysis

  • Medical decision support

Workshop Programme

The workshop will feature:

• Invited keynote speakers from academia (Stephan Günnemann, Technische Universität München) and industry (Fabien Gaire, Roche).

• Oral presentations

• A poster session

The full programme will be posted on the workshop's website in due course.

Important dates

• Submission Deadline: June 30, 2020 [Extended from June 11, 2020]

• Notification: July 24, 2020 [Extended from July 09, 2020]

• Workshop date: Monday 14th of September

• Workshop format: There is the possibility of having a fully virtual (online) event