KDH 2019
International Workshop on Knowledge Discovery in Healthcare Data

Table of Contents

• Preface
  
  

Frameworks and Repositories

• Correcting Crowdsourced Annotations to Improve Detection of Outcome Types in Evidence Based Medicine 1-5
  Micheal Abaho, Danushka Bollegala, Paula Williamson, Susanna Dodd
• Analysing the Heterogeneity of Rule-Based EHR Phenotyping Algorithms in CALIBER and the UK Biobank 6-14
  Spiros Denaxas, Helen Parkinson, Natalie Fitzpatrick, Cathie Sudlow, Harry Hemingway

Machine Learning and Classification

• Explaining Deep Classification of Time-Series Data with Learned Prototypes 15-22
  Alan H. Gee, Diego Garcia-Olano, Joydeep Ghosh, David Paydarfar
• Feature Visualisation of Classification of Diabetic Retinopathy Using a Convolutional Neural Network 23-29
  Harry Pratt, Frans Coenen, Simon P. Harding, Deborah M. Broadbent, Yalin Zheng
• Tick Parasitism Classification from Noisy Medical Records 30-34
  James O ' Neill, Danushka Bollegala, Peter Noble, Alan Radford
• Learning to Detect Heavy Drinking Episodes Using Smartphone Accelerometer Data 35-42
  Jackson A. Killian, Kevin M. Passino, Arnab Nandi, Danielle R. Madden, John Clapp

Applications

• Learning Reliable Policies in the Bandit Setting with Application to Adaptive Clinical Trials 43-49
  Hossein Aboutalebi, Doina Precup, Tibor Schuster
• Extracting Supporting Evidence from Medical Negligence Claim Texts 50-54
  Robert Bevan, Alessandro Torrisi, Danushka Bollegala, Frans Coenen, Katie Atkinson
• Predicting ICU Mortality from Heterogeneous Clinical Events with Prior Medical Knowledge 55-59
  Lujing Xiao, Chuanpan Zheng, Xiaoliang Fan, Yi Xie, Rongshan Yu

Position Papers

• Learning to Self-Manage by Intelligent Monitoring, Prediction and Intervention 60-67
  Nirmalie Wiratunga, David Corsar, Kyle Martin, Anjana Wijekoon, Eyad Elyan, Kay Cooper, Zina Ibrahim, Oya Celikutan, Richard Dobson, Stephen McKenna, Jacqui Morris, Annalu Waller, Raed Abd-Alhammed, Rami Qahwaji, Ray Chaudhuri