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ORCID19th AIME 2021: Virtual Event
- Allan Tucker
, Pedro Henriques Abreu, Jaime S. Cardoso, Pedro Pereira Rodrigues, David Riaño:
Artificial Intelligence in Medicine - 19th International Conference on Artificial Intelligence in Medicine, AIME 2021, Virtual Event, June 15-18, 2021, Proceedings. Lecture Notes in Computer Science 12721, Springer 2021, ISBN 978-3-030-77210-9
Invited Talk
- Virginia Dignum:
The Myth of Complete AI-Fairness. 3-8
Image Analysis
- Jerry W. Wei, Arief A. Suriawinata, Bing Ren, Xiaoying Liu, Mikhail Lisovsky, Louis J. Vaickus, Charles Brown, Michael Baker, Naofumi Tomita, Lorenzo Torresani, Jason Wei, Saeed Hassanpour:
A Petri Dish for Histopathology Image Analysis. 11-24 - David Calhas, Rui Henriques:
fMRI Multiple Missing Values Imputation Regularized by a Recurrent Denoiser. 25-35 - Biraja Ghoshal, Stephen Swift, Allan Tucker:
Bayesian Deep Active Learning for Medical Image Analysis. 36-42 - Giulia Campi, Giovanna Nicora, Giulia Fiorentino, Andrew Smith, Fulvio Magni, Silvia Garagna, Maurizio Zuccotti, Riccardo Bellazzi:
A Topological Data Analysis Mapper of the Ovarian Folliculogenesis Based on MALDI Mass Spectrometry Imaging Proteomics. 43-47
Predictive Modelling
- Mohammadreza Nemati, Haonan Zhang, Michael Sloma, Dulat Bekbolsynov, Hong Wang, Stanislaw Stepkowski, Kevin S. Xu:
Predicting Kidney Transplant Survival Using Multiple Feature Representations for HLAs. 51-60 - Moritz Kulessa, Bennet Wittelsbach, Eneldo Loza Mencía, Johannes Fürnkranz:
Sum-Product Networks for Early Outbreak Detection of Emerging Diseases. 61-71 - Aneta Lisowska, Szymon Wilk, Mor Peleg:
Catching Patient's Attention at the Right Time to Help Them Undergo Behavioural Change: Stress Classification Experiment from Blood Volume Pulse. 72-82 - Goce Ristanoski, Jon Emery, Javiera Martinez-Gutierrez, Damien McCarthy, Uwe Aickelin:
Primary Care Datasets for Early Lung Cancer Detection: An AI Led Approach. 83-92 - Davy Weissenbacher, Siddharth Rawal, Arjun Magge, Graciela Gonzalez-Hernandez:
Addressing Extreme Imbalance for Detecting Medications Mentioned in Twitter User Timelines. 93-102 - David Cuadrado, David Riaño:
ICU Days-to-Discharge Analysis with Machine Learning Technology. 103-113 - Vithya Yogarajan, Jacob Montiel, Tony Smith, Bernhard Pfahringer:
Transformers for Multi-label Classification of Medical Text: An Empirical Comparison. 114-123 - William Van Woensel, Manal Elnenaei, Syed Ali Imran, Syed Sibte Raza Abidi:
Semantic Web Framework to Computerize Staged Reflex Testing Protocols to Mitigate Underutilization of Pathology Tests for Diagnosing Pituitary Disorders. 124-134 - Mohammadamin Tajgardoon, Shyam Visweswaran:
Using Distribution Divergence to Predict Changes in the Performance of Clinical Predictive Models. 135-145 - Yuki Oba, Taro Tezuka, Masaru Sanuki, Yukiko Wagatsuma:
Analysis of Health Screening Records Using Interpretations of Predictive Models. 146-151 - Bernardo Cánovas-Segura, Antonio Morales Nicolás, José M. Juárez, Manuel Campos:
Seasonality in Infection Predictions Using Interpretable Models for High Dimensional Imbalanced Datasets. 152-156 - Dympna O'Sullivan, Rilwan Remilekun Basaru, Simone Stumpf, Neil A. M. Maiden:
Monitoring Quality of Life Indicators at Home from Sparse, and Low-Cost Sensor Data. 157-162 - Marco Cotogni, Lucia Sacchi, Dejan Georgiev, Aleksander Sadikov:
Detection of Parkinson's Disease Early Progressors Using Routine Clinical Predictors. 163-167 - Alessia Gerbasi, Vida Groznik, Dejan Georgiev, Lucia Sacchi, Aleksander Sadikov:
Detecting Mild Cognitive Impairment Using Smooth Pursuit and a Modified Corsi Task. 168-172
Temporal Data Analysis
- Jeongmin Lee, Milos Hauskrecht:
Neural Clinical Event Sequence Prediction Through Personalized Online Adaptive Learning. 175-186 - Joseph Miano, Charity Hilton, Vasu Gangrade, Mary Pomeroy, Jacqueline Siven, Michael Flynn, Frances Tilashalski:
Using Event-Based Web-Scraping Methods and Bidirectional Transformers to Characterize COVID-19 Outbreaks in Food Production and Retail Settings. 187-198 - Miguel Rios, Ameen Abu-Hanna:
Deep Kernel Learning for Mortality Prediction in the Face of Temporal Shift. 199-208 - Lee B. Hinkle, Vangelis Metsis:
Model Evaluation Approaches for Human Activity Recognition from Time-Series Data. 209-215
Unsupervised Learning
- Melanie Hackl, Suparno Datta, Riccardo Miotto, Erwin P. Böttinger:
Unsupervised Learning to Subphenotype Heart Failure Patients from Electronic Health Records. 219-228 - Anita Valmarska, Nada Lavrac, Marko Robnik-Sikonja:
Stratification of Parkinson's Disease Patients via Multi-view Clustering. 229-239 - Cheng Cheng, Jason N. Kennedy, Christopher W. Seymour, Jeremy C. Weiss:
Disentangled Hyperspherical Clustering for Sepsis Phenotyping. 240-245 - Antonio Lopez-Martinez-Carrasco, Jose M. Juarez, Manuel Campos, Bernardo Cánovas-Segura:
Phenotypes for Resistant Bacteria Infections Using an Efficient Subgroup Discovery Algorithm. 246-251 - Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, David Page, Sriraam Natarajan:
Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach. 252-257 - Xin Tan, Yanwan Dai, Ahmed Imtiaz Humayun, Haoze Chen, Genevera I. Allen, Parag N. Jain:
Detection of Junctional Ectopic Tachycardia by Central Venous Pressure. 258-262
Planning and Decision Support
- Diogo Nogueira-Leite, João Miguel Alves, Manuel Marques-Cruz, Ricardo Cruz-Correia:
A Cautionary Tale on Using Covid-19 Data for Machine Learning. 265-275 - Martin Michalowski, Malvika Rao, Szymon Wilk, Wojtek Michalowski, Marc Carrier:
MitPlan 2.0: Enhanced Support for Multi-morbid Patient Management Using Planning. 276-286 - Milene Santos Teixeira, Ivan Donadello, Mauro Dragoni:
Explanations in Digital Health: The Case of Supporting People Lifestyles. 287-292 - Kain Kordian Gontarska, Weronika Wrazen, Jossekin Beilharz, Robert Schmid, Lauritz Thamsen, Andreas Polze:
Predicting Medical Interventions from Vital Parameters: Towards a Decision Support System for Remote Patient Monitoring. 293-297 - Enea Parimbelli, Matteo Gabetta, Giordano Lanzola, Francesca Polce, Szymon Wilk, David Glasspool, Alexandra Kogan, Roy Leizer, Vitali Gisko, Nicole Veggiotti, Silvia Panzarasa, Rowdy de Groot, Manuel Ottaviano, Lucia Sacchi, Ronald Cornet, Mor Peleg, Silvana Quaglini:
CAncer PAtients Better Life Experience (CAPABLE) First Proof-of-Concept Demonstration. 298-303
Deep Learning
- Manu Goyal, Judith Austin-Strohbehn, Sean J. Sun, Karen Rodriguez, Jessica M. Sin, Yvonne Y. Cheung, Saeed Hassanpour:
Sensitivity and Specificity Evaluation of Deep Learning Models for Detection of Pneumoperitoneum on Chest Radiographs. 307-317 - Mattia Chiari, Alfonso Emilio Gerevini, Matteo Olivato, Luca Putelli, Nicholas Rossetti, Ivan Serina:
An Application of Recurrent Neural Networks for Estimating the Prognosis of COVID-19 Patients in Northern Italy. 318-328 - Enrico Longato, Gian Paolo Fadini, Giovanni Sparacino, Angelo Avogaro, Barbara Di Camillo:
Recurrent Neural Network to Predict Renal Function Impairment in Diabetic Patients via Longitudinal Routine Check-up Data. 329-337 - Zhendong Wang, Isak Samsten, Panagiotis Papapetrou:
Counterfactual Explanations for Survival Prediction of Cardiovascular ICU Patients. 338-348 - Himanshu K. Gajera, Mukesh A. Zaveri, Deepak Ranjan Nayak:
Improving the Performance of Melanoma Detection in Dermoscopy Images Using Deep CNN Features. 349-354 - Yaroub Elloumi:
Mobile Aided System of Deep-Learning Based Cataract Grading from Fundus Images. 355-360 - Bhargab Ghoshal, Biraja Ghoshal, Stephen Swift, Allan Tucker:
Uncertainty Estimation in SARS-CoV-2 B-Cell Epitope Prediction for Vaccine Development. 361-366 - Luca Putelli, Alfonso Emilio Gerevini, Alberto Lavelli, Roberto Maroldi, Ivan Serina:
Attention-Based Explanation in a Deep Learning Model For Classifying Radiology Reports. 367-372 - José G. P. Lima, Geraldo Braz Junior, João Dallyson Sousa de Almeida, Caio Eduardo Falcão Matos:
Evaluation of Encoder-Decoder Architectures for Automatic Skin Lesion Segmentation. 373-377 - Amir Bouden, Ahmed Ghazi Blaiech, Khaled Ben Khalifa, Asma Ben Abdallah, Mohamed Hédi Bedoui:
A Novel Deep Learning Model for COVID-19 Detection from Combined Heterogeneous X-ray and CT Chest Images. 378-383 - Nils Gumpfer, Joshua Prim, Dimitri Grün, Jennifer Hannig, Till Keller, Michael Guckert:
An Experiment Environment for Definition, Training and Evaluation of Electrocardiogram-Based AI Models. 384-388 - Yan Jia, John A. McDermid, Ibrahim Habli:
Enhancing the Value of Counterfactual Explanations for Deep Learning. 389-394
Natural Language Processing
- Nikolaos Mylonas, Stamatis Karlos, Grigorios Tsoumakas:
A Multi-instance Multi-label Weakly Supervised Approach for Dealing with Emerging MeSH Descriptors. 397-407 - Aynur Guluzade, Endri Kacupaj, Maria Maleshkova:
Demographic Aware Probabilistic Medical Knowledge Graph Embeddings of Electronic Medical Records. 408-417 - Loïc Etienne, Francis Faux, Olivier Roecker:
Modeling and Representation by Graphs of the Reasoning of an Emergency Doctor: Symptom Checker MedVir. 418-427 - Perceval Wajsbürt, Yoann Taillé, Xavier Tannier:
Effect of Depth Order on Iterative Nested Named Entity Recognition Models. 428-432 - Torec T. Luik, Miguel Rios, Ameen Abu-Hanna, Henk C. P. M. van Weert, Martijn C. Schut:
The Effectiveness of Phrase Skip-Gram in Primary Care NLP for the Prediction of Lung Cancer. 433-437 - John Pavlopoulos, Panagiotis Papapetrou:
Customized Neural Predictive Medical Text: A Use-Case on Caregivers. 438-443 - Chee Keong Wee, Nathan Wee:
Outlier Detection for GP Referrals in Otorhinolaryngology. 444-451 - Oliver Hijano Cubelos, Thomas Balezeau, Julien Guerin:
The Champollion Project: Automatic Structuration of Clinical Features from Medical Records. 452-456
Knowledge Representation and Rule Mining
- David Riaño, Aida Kamisalic:
Modelling and Assessment of One-Drug Dose Titration. 459-468 - Biplob Biswas, Thai-Hoang Pham, Ping Zhang:
TransICD: Transformer Based Code-Wise Attention Model for Explainable ICD Coding. 469-478 - Matthew Barren, Milos Hauskrecht:
Improving Prediction of Low-Prior Clinical Events with Simultaneous General Patient-State Representation Learning. 479-490 - Mikayla Biggs, Carla Floricel, Lisanne van Dijk, Abdallah Sherif Radwan Mohamed, Clifton David Fuller, G. Elisabeta Marai, Xinhua Zhang, Guadalupe Canahuate:
Identifying Symptom Clusters Through Association Rule Mining. 491-496 - Athresh Karanam, Alexander L. Hayes, Harsha Kokel, David M. Haas, Predrag Radivojac, Sriraam Natarajan:
A Probabilistic Approach to Extract Qualitative Knowledge for Early Prediction of Gestational Diabetes. 497-502
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