Abstract is missing.
- Interactive Explanations of Internal Representations of Neural Network Layers: An Exploratory Study on Outcome Prediction of Comatose PatientsMeike Nauta, Michel van Putten, Marleen C. Tjepkema-Cloostermans, Jeroen Bos, Maurice van Keulen, Christin Seifert. 5-11 [doi]
- Comparison of Forecasting Algorithms for Type 1 Diabetic Glucose Prediction on 30 and 60-Minute Prediction HorizonsRichard McShinsky, Brandon Marshall. 12-18 [doi]
- Uncertainty Quantification in Chest X-Ray Image Classification using Bayesian Deep Neural NetworksYumin Liu, Claire Zhao, Jonathan Rubin. 19-26 [doi]
- Prognosis Prediction in Covid-19 Patients from Lab Tests and X-ray Data through Randomized Decision TreesAlfonso Emilio Gerevini, Roberto Maroldi, Matteo Olivato, Luca Putelli, Ivan Serina. 27-34 [doi]
- Knowledge Discovery and Visualization in Healthcare Datasets using Formal Concept Analysis and Graph DatabasesDiana Cristea, Christian Sacarea, Diana-Florina Sotropa. 35-42 [doi]
- A General Neural Architecture for Carbohydrate and Bolus Recommendations in Type 1 Diabetes ManagementJeremy Beauchamp, Razvan C. Bunescu, Cindy Marling. 43-47 [doi]
- Region Proposal Network for Lung Nodule Detection and SegmentationMohammad Hesam Hesamian, Wenjing Jia, Sean He, Paul J. Kennedy. 48-52 [doi]
- In Silico Comparison of Continuous Glucose Monitor Failure Mode Strategies for an Artificial PancreasYunjie Lisa Lu, Abigail Koay, Michael Mayo. 53-57 [doi]
- Towards Causal Knowledge Graphs - Position PaperEva Blomqvist, Marjan Alirezaie, Marina Santini. 58-62 [doi]
- Assessing the Clinicians' Pathway to Embed Artificial Intelligence for Assisted Diagnostics of Fracture DetectionCarlos Francisco Moreno-García, Truong Dang, Kyle Martin, Manish Patel, Andrew Thompson 0008, Lesley Leishman, Nirmalie Wiratunga. 63-70 [doi]
- The OhioT1DM Dataset for Blood Glucose Level Prediction: Update 2020Cindy Marling, Razvan C. Bunescu. 71-74 [doi]
- A Personalized and Interpretable Deep Learning Based Approach to Predict Blood Glucose Concentration in Type 1 DiabetesGiacomo Cappon, Lorenzo Meneghetti, Francesco Prendin, Jacopo Pavan, Giovanni Sparacino, Simone Del Favero, Andrea Facchinetti. 75-79 [doi]
- Neural Multi-class Classification Approach to Blood Glucose Level Forecasting with Prediction Uncertainty VisualisationMichael Mayo, Tomas Koutny. 80-84 [doi]
- Investigating Potentials and Pitfalls of Knowledge Distillation Across Datasets for Blood Glucose ForecastingHadia Hameed, Samantha Kleinberg. 85-89 [doi]
- Blood Glucose Prediction for Type 1 Diabetes Using Generative Adversarial NetworksTaiyu Zhu, Xi Yao, Kezhi Li, Pau Herrero, Pantelis Georgiou. 90-94 [doi]
- Personalized Machine Learning Algorithm based on Shallow Network and Error Imputation Module for an Improved Blood Glucose PredictionJacopo Pavan, Francesco Prendin, Lorenzo Meneghetti, Giacomo Cappon, Giovanni Sparacino, Andrea Facchinetti, Simone Del Favero. 95-99 [doi]
- Experiments in Non-Personalized Future Blood Glucose Level PredictionRobert Bevan, Frans Coenen. 100-104 [doi]
- Deep Residual Time-Series Forecasting: Application to Blood Glucose PredictionHarry Rubin-Falcone, Ian Fox, Jenna Wiens. 105-109 [doi]
- Personalised Glucose Prediction via Deep Multitask NetworksJohn Daniels, Pau Herrero, Pantelis Georgiou. 110-114 [doi]
- Prediction of Blood Glucose Levels for People with Type 1 Diabetes using Latent-Variable-based ModelXiaoyu Sun, Mudassir M. Rashid, Mert Sevil, Nicole Hobbs, Rachel Brandt, Mohammad-Reza Askari, Andrew Shahidehpour, Ali Cinar. 115-119 [doi]
- Data Fusion of Activity and CGM for Predicting Blood Glucose LevelsHoda Nemat, Heydar Khadem, Jackie Elliott, Mohammed Benaissa. 120-124 [doi]
- Blood Glucose Level Prediction as Time-Series Modeling using Sequence-to-Sequence Neural NetworksAnanth Reddy Bhimireddy, Priyanshu Sinha, Bolu Oluwalade, Judy Wawira Gichoya, Saptarshi Purkayastha. 125-130 [doi]
- A Deep Learning Approach for Blood Glucose Prediction and Monitoring of Type 1 Diabetes PatientsJonas Freiburghaus, Aïcha Rizzotti-Kaddouri, Fabrizio Albertetti. 131-135 [doi]
- Multi-Scale Long Short-Term Memory Network with Multi-Lag Structure for Blood Glucose PredictionTao Yang, Ruikun Wu, Rui Tao, Shuang Wen, Ning Ma, Yuhang Zhao, Xia Yu, Hongru Li. 136-140 [doi]
- Analysis of the performance of Genetic Programming on the Blood Glucose Level Prediction Challenge 2020David Joedicke, Gabriel Kronberger, José Manuel Colmenar, Stephan M. Winkler, José Manuel Velasco, Sergio Contador, José Ignacio Hidalgo. 141-145 [doi]
- Multi-lag Stacking for Blood Glucose Level PredictionHeydar Khadem, Hoda Nemat, Jackie Elliott, Mohammed Benaissa. 146-150 [doi]
- Online Blood Glucose Prediction Using Autoregressive Moving Average Model with Residual Compensation NetworkNing Ma, Yuhang Zhao, Shuang Wen, Tao Yang, Ruikun Wu, Rui Tao, Xia Yu, Hongru Li. 151-155 [doi]