PharML 2020
Machine Learning for Pharma and Healthcare Applications
ECML PKDD 2020 Workshop
September 14 at 14:00 hs (CEST)
Accepted Submissions
Greta Markert (IBM, Zurich Research Laboratory and ETH Zurich), Jannis Born (IBM, Zurich Research Laboratory and ETH Zurich), Matteo Manica (IBM, Zurich Research Laboratory), Gisbert Schneider (ETH Zurich) and Maria Rodriguez Martinez (IBM, Zurich Research Laboratory) . Chemical Representation Learning for Toxicity Prediction
Konstantinos Pliakos (Katholieke Universiteit Leuven) and Celine Vens (Katholieke Universiteit Leuven). Drug-target interaction prediction with tree-ensembles on reconstructed networks
Amina Mollaysa (HES-SO & University of Geneva), Brooks Paige (UCL & The Alan Turing Institute) and Alexandros Kalousis (HES-SO & University of Geneva). Goal-directed Generation of Molecules
Robert-George Colț (Romanian Institute of Science and Technology), Csongor-Huba Várady (Romanian Institute of Science and Technology), Riccardo Volpi (Romanian Institute of Science and Technology), Luigi Malagò (Romanian Institute of Science and Technology). Automatic Feature Extraction for Phonocardiogram Heartbeat Anomaly Detection using WaveNet VAE
Hugo De Oliveira (HEVA), Alexandre Batisse (HEVA), Julien Beisel (HEVA), Marie Laurent (HEVA) and Martin Prodel (HEVA). Meta-TAK: a scalable double-clustering method for treatment sequence visualization
Lucas Giovanni Uberti-Bona Marin (Maastricht University and PNA) and Rachel Cavill (Maastricht University). Learning to learn: a drug resistance learning pipeline
Taehoon Kim (ETH Zurich), Philipp Hornauer (ETH Zurich), Christian Donner (Swiss Data Science Center), Andreas Hierlemann, Karsten Borgwardt (ETH Zurich), Manuel Schröter (ETH Zurich) and Damian Roqueiro (ETH Zurich). Comparison of connectivity inference algorithms for classification of neuronal cultures using graph kernels
Bin Liu (Aristotle University of Thessaloniki), Konstantinos Pliakos (KU Leuven and ITEC), Celine Vens (KU Leuven and ITEC) and Grigorios Tsoumakas (Aristotle University of Thessaloniki). Local Imbalance based Ensemble for Predicting Interactions between Novel Drugs and Targets
Konstantinos Papangelou (Unversity of Manchester) and Konstantinos Sechidis (Novartis Pharma A.G.). A Multi-objective Evaluation Framework for Subgroup Identification Algorithms
Youyi Zhang (AstraZeneca), Sreenath Nampally (AstraZeneca), Emmette Hutchison (AstraZeneca), Jim Weatherall (AstraZeneca), Faisal Khan (AstraZeneca) and Khader Shameer (AstraZeneca). Predictive Modeling of Personalized Clinical Trial Attrition using Time-to-event Approaches
Alexandra-Ioana Albu (Romanian Institute of Science and Technology and Babes-Bolyai University), Alina Enescu (Romanian Institute of Science and Technology and Babes-Bolyai University) and Luigi Malago (Romanian Institute of Science and Technology). Detection of Tumours in Brain MRIs with Variational AutoEncoders
Arvind Pillai (AstraZeneca), Halsey Lea (AstraZeneca), Faisal Khan (AstraZeneca) and Glynn Dennis (AstraZeneca), Personaized Step Counting Using Wearable Sensors: A Domain Adapted LSTM Network Approach
Nikolaos Nikolaou (University College London) and Konstantinos Sechidis (Novartis Pharma A.G.). Inferring Causal Direction from Observational Data: A Complexity Approach
Annika Pick (Fraunhofer), Sebastian Ginzel (Fraunhofer), Stefan Rüping (Fraunhofer), Jil Sander (Fraunhofer), Ann Christina Foldenauer (Fraunhofer) and Michaela Köhm (Fraunhofer). Aligning Subjective Ratings in Clinical Decision Making