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ORCIDKDH@ECAI 2020: Santiago de Compostela, Spain
- Kerstin Bach, Razvan C. Bunescu, Cindy Marling, Nirmalie Wiratunga:
Proceedings of the 5th International Workshop on Knowledge Discovery in Healthcare Data co-located with 24th European Conference on Artificial Intelligence, KDH@ECAI 2020, Santiago de Compostela, Spain & Virtually, August 29-30, 2020. CEUR Workshop Proceedings 2675, CEUR-WS.org 2020
KDH 2020 Technical Papers
- Meike Nauta, Michel J. A. M. van Putten, Marleen C. Tjepkema-Cloostermans, Jeroen Bos, Maurice van Keulen, Christin Seifert:
Interactive Explanations of Internal Representations of Neural Network Layers: An Exploratory Study on Outcome Prediction of Comatose Patients. 5-11 - Richard McShinsky, Brandon Marshall:
Comparison of Forecasting Algorithms for Type 1 Diabetic Glucose Prediction on 30 and 60-Minute Prediction Horizons. 12-18 - Yumin Liu, Claire Zhao, Jonathan Rubin:
Uncertainty Quantification in Chest X-Ray Image Classification using Bayesian Deep Neural Networks. 19-26 - Alfonso Emilio Gerevini, Roberto Maroldi, Matteo Olivato, Luca Putelli, Ivan Serina:
Prognosis Prediction in Covid-19 Patients from Lab Tests and X-ray Data through Randomized Decision Trees. 27-34 - Diana Cristea, Christian Sacarea, Diana-Florina Sotropa:
Knowledge Discovery and Visualization in Healthcare Datasets using Formal Concept Analysis and Graph Databases. 35-42 - Jeremy Beauchamp, Razvan C. Bunescu, Cindy Marling:
A General Neural Architecture for Carbohydrate and Bolus Recommendations in Type 1 Diabetes Management. 43-47 - Mohammad Hesam Hesamian, Wenjing Jia, Sean He, Paul J. Kennedy:
Region Proposal Network for Lung Nodule Detection and Segmentation. 48-52 - Yunjie Lisa Lu, Abigail Koay, Michael Mayo:
In Silico Comparison of Continuous Glucose Monitor Failure Mode Strategies for an Artificial Pancreas. 53-57 - Eva Blomqvist, Marjan Alirezaie, Marina Santini:
Towards Causal Knowledge Graphs - Position Paper. 58-62 - Carlos Francisco Moreno-García, Truong Dang, Kyle Martin, Manish Patel, Andrew Thompson, Lesley Leishman, Nirmalie Wiratunga:
Assessing the Clinicians' Pathway to Embed Artificial Intelligence for Assisted Diagnostics of Fracture Detection. 63-70
Blood Glucose Level Prediction Challenge Papers
- Cindy Marling, Razvan C. Bunescu:
The OhioT1DM Dataset for Blood Glucose Level Prediction: Update 2020. 71-74 - Giacomo Cappon, Lorenzo Meneghetti, Francesco Prendin, Jacopo Pavan, Giovanni Sparacino, Simone Del Favero, Andrea Facchinetti:
A Personalized and Interpretable Deep Learning Based Approach to Predict Blood Glucose Concentration in Type 1 Diabetes. 75-79 - Michael Mayo, Tomas Koutny:
Neural Multi-class Classification Approach to Blood Glucose Level Forecasting with Prediction Uncertainty Visualisation. 80-84 - Hadia Hameed, Samantha Kleinberg:
Investigating Potentials and Pitfalls of Knowledge Distillation Across Datasets for Blood Glucose Forecasting. 85-89 - Taiyu Zhu, Xi Yao, Kezhi Li, Pau Herrero, Pantelis Georgiou:
Blood Glucose Prediction for Type 1 Diabetes Using Generative Adversarial Networks. 90-94 - Jacopo Pavan, Francesco Prendin, Lorenzo Meneghetti, Giacomo Cappon, Giovanni Sparacino, Andrea Facchinetti, Simone Del Favero:
Personalized Machine Learning Algorithm based on Shallow Network and Error Imputation Module for an Improved Blood Glucose Prediction. 95-99 - Robert Bevan, Frans Coenen:
Experiments in Non-Personalized Future Blood Glucose Level Prediction. 100-104 - Harry Rubin-Falcone, Ian Fox, Jenna Wiens:
Deep Residual Time-Series Forecasting: Application to Blood Glucose Prediction. 105-109 - John Daniels, Pau Herrero, Pantelis Georgiou:
Personalised Glucose Prediction via Deep Multitask Networks. 110-114 - Xiaoyu Sun, Mudassir M. Rashid, Mert Sevil, Nicole Hobbs, Rachel Brandt, Mohammad-Reza Askari, Andrew Shahidehpour, Ali Cinar:
Prediction of Blood Glucose Levels for People with Type 1 Diabetes using Latent-Variable-based Model. 115-119 - Hoda Nemat, Heydar Khadem, Jackie Elliott, Mohammed Benaissa:
Data Fusion of Activity and CGM for Predicting Blood Glucose Levels. 120-124 - Ananth Reddy Bhimireddy, Priyanshu Sinha, Bolu Oluwalade, Judy Wawira Gichoya, Saptarshi Purkayastha:
Blood Glucose Level Prediction as Time-Series Modeling using Sequence-to-Sequence Neural Networks. 125-130 - Jonas Freiburghaus, Aïcha Rizzotti-Kaddouri, Fabrizio Albertetti
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A Deep Learning Approach for Blood Glucose Prediction and Monitoring of Type 1 Diabetes Patients. 131-135 - Tao Yang, Ruikun Wu, Rui Tao, Shuang Wen, Ning Ma, Yuhang Zhao, Xia Yu, Hongru Li:
Multi-Scale Long Short-Term Memory Network with Multi-Lag Structure for Blood Glucose Prediction. 136-140 - David Joedicke, Gabriel Kronberger, José Manuel Colmenar, Stephan M. Winkler, José Manuel Velasco, Sergio Contador, José Ignacio Hidalgo:
Analysis of the performance of Genetic Programming on the Blood Glucose Level Prediction Challenge 2020. 141-145 - Heydar Khadem, Hoda Nemat, Jackie Elliott, Mohammed Benaissa:
Multi-lag Stacking for Blood Glucose Level Prediction. 146-150 - Ning Ma, Yuhang Zhao, Shuang Wen, Tao Yang, Ruikun Wu, Rui Tao, Xia Yu, Hongru Li:
Online Blood Glucose Prediction Using Autoregressive Moving Average Model with Residual Compensation Network. 151-155
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