Accepted Papers
Vishal Vinod, Susmit Agrawal, Vipul Gaurav, Pallavi R and Savita Choudhary. Multilingual Medical Question Answering and Information Retrieval for Rural Health Intelligence Access. [PDF]
Kathleen Lois Foster and Alessandro Maria Selvitella. Government measures against the COVID-19 pandemic must be determined according to the socio-economic status of the country. [PDF]
Alessandro Maria Selvitella and Kathleen Lois Foster. A higher-order Taylor expansion of the initial trajectory of COVID-19 cases and deaths via Bayesian hierarchical models: a toy problem and possible public health insights.. [PDF]
Rong-Ching Chang, Chun-Ming Lai, Chu-Hsing Lin and Kai-Chih Pai. ONLINE SENTIMENT AND REACTIONS TO POSTS ON FACEBOOK: LEADING INDICATORS FOR STATE-LEVEL COVID-19 CONFIRMED CASES. [PDF]
Laura Manduchi, Ričards Marcinkevičs and Julia E. Vogt. A Deep Variational Approach to Clustering Survival Data. [PDF]
Giulia Marchello, Audrey Fresse, Marco Corneli and Charles Bouveyron. Co-clustering of evolving count matrices in pharmacovigilance with the dynamic latent block model. [PDF]
Pallika Kanani, Virendra Marathe, Daniel Peterson, Rave Harpaz and Steve Bright. PRIVATE CROSS-SILO FEDERATED LEARNING FOR EXTRACTING VACCINE ADVERSE EVENT MENTIONS. [PDF]
Dipam Paul, Alankrita Tewari, Jiwoong Jeong and Imon Banerjee. Boosting Classification Accuracy of Fertile Sperm Cell Images leveraging cDCGAN. [PDF]
Dennis Núñez-Fernández, Lamberto Ballan, Gabriel Jiménez-Avalos, Jorge Coronel, Patricia Sheen and Mirko Zimic. Prediction of Tuberculosis using U-Net and segmentation techniques. [PDF]
Yuhao Qian, Yihe Yang, Junfeng Zhi and Dianbo Liu. Structure agnostic federated learning by adaptable gradient descent. [PDF]
Sekou Remy and Oliver Bent. LEARNING TO ACT: NOVEL INTEGRATION OF ALGORITHMS AND MODELS FOR EPIDEMIC PREPAREDNESS. [PDF]
Diyuan Lu, Gerhard Kurz, Nenad Polomac, Iskra Gacheva, Elke Hattingen and Jochen Triesch. Multiple Instance-Based Tumor Detection from Magnetic Resonance Spectroscopy Data. [PDF]
Hannes Stärk, Christian Dallago, Michael Heinzinger and Burkhard Rost. Light Attention Predicts Protein Location from the Language of Life. [PDF]
Alessandro Maria Selvitella and Kathleen Lois Foster. Bayesian detection and uncertainty quantification of the first change point of the COVID-19 case curve in the Midwest: Timeliness of non-pharmaceutical interventions.. [PDF]
Naveen Durvasula, John Dickerson and Aravind Srinivasan. A Bayesian Optimization Approach to Estimating Expected Match Time and Organ Quality in Kidney Exchange. [PDF]
Joao Palotti, Ignacio Perez Pozuelo, Abdulaziz Al Homaid, Raghvendra Mall, Marius Posa, Heather Berlin, Di Jin, Faisal Farooq and Peter Szolovits. Predicting Several Sleep Quality Metrics based on Same Day Physical Activity. [PDF]
Raafia Ahmed, Corinne Stroum, Rylan Larsen, Jasmine Wilkerson, Carly Eckert, Shoeb Sitafalwalla, Naveed Moosa and Tina Esposito. Prevalence of Undiagnosed Diabetes Type 2 and Social Risk Factors Among Communities with Diagnosis Disparities. [PDF]
Haidong Yi and Natalie Stanley. CytoSet: a deep learning model for predicting clinical outcomes from cytometry data. [PDF]
Nishant Yadav and Auroop R. Ganguly. BAYESIAN LEARNING TO QUANTIFY IMPACTS OF COVID-19 LOCKDOWNS ON URBAN AIR QUALITY. [PDF]
Saahil Sundaresan. Informing on Public Health Effects and Dining Risks as the COVID-19 Threat Evolves: A Data-driven Approach. [PDF]
Nidhi Mulay, Vikas Bishnoi, Himanshi Charotia, Siddhartha Asthana, Gaurav Dhama and Ankur Arora. Pandemic spread prediction and healthcare preparedness through financial and mobility data. [PDF]
Hongyuan Dong, Jiaqing Xie, Zhi Jing and Dexin Ren. Variational Autoencoder for Anti-Cancer Drug Response Prediction. [PDF]
Xiao Liu, Anjana Susarla and Rema Padman. Machine Learning Approaches for Accessible Public Health Information about COVID-19. [PDF]
Jakub Bartoszewicz, Anja Seidel and Bernhard Renard. Interpretable prediction of the infectious potential of novel viruses. [PDF]
Niklas Smedemark-Margulies, Robin Walters, Heiko Zimmermann, Lucas Laird, Neela Kaushik, Rajmonda Caceres and Jan-Willem van de Meent. Inference in Network-based Epidemiological Simulations with Probabilistic Programming. [PDF]
Qiang Li, Lily Xu and Corin Otesteanu. All you need is Cell Attention: A Cell Annotation Tool for Single-Cell Morphology Data. [PDF]
Isaac Neal, Sohan Seth, Gary Watmough and Mamadou Saliou Diallo. Towards Sustainable Census Independent Population Estimation in Mozambique. [PDF]
Sanja Scepanovic, Luca Maria Aiello, Ke Zhou and Daniele Quercia. Creating a health taxonomy with social media. [PDF]
Ayush Deva, Siddhant Shingi, Avtansh Tiwari, Nayana Bannur, Sansiddh Jain, Jerome White, Alpan Raval and Srujana Merugu. Interpretability of Epidemiological Models: The Curse of Non-Identifiability. [PDF]
Balaji Radhakrishnan, Ankit Murarka and Sushma Ravichandran. CLASSIFICATION OF MENTAL ILLNESSES ON SOCIAL MEDIA USING ROBERTA. [PDF]
Paolo Bertolotti and Ali Jadbabaie. Network Group Testing. [PDF]
Krzysztof Maziarz, Anna Krason and Zbigniew Wojna. Deep Learning for Rheumatoid Arthritis: Joint Detection and Damage Scoring in X-rays. [PDF]
Dianbo Liu and Tim Miller. Federated pretraining and fine tuning of BERT using clinical notes from multiple silos. [PDF]
Wuraola Fisayo Oyewusi, Olubayo Adekanmbi, Ifeoma Okoh, Mary Idera Salami, Opeyemi Osakuade, Sharon Ibejih and Vitus Onuigwe. Artificial Intelligence for Pharmacovigilance in Nigerian Social Media Text. [PDF]
Arnab Sarker, Ali Jadbabaie and Devavrat Shah. Mixtures Matter: Interpretable Forecasting for Epidemics. [PDF]
Makkunda Sharma, Nikhil Shenoy, Jigar Doshi, Piyush Bagad, Aman Dalmia, Parag Bhamare, Amrita Mahale, Saurabh Rane, Neeraj Agrawal and Rahul Panicker. Impact of data-splits on generalization: Identifying COVID-19 from cough and context. [PDF]
Ngan Thi Dong and Megha Khosla. A multitask transfer learning framework for Novel virus-human protein interactions. [PDF] Yuhao Qian, Yihe Yang, Junfeng Zhi and Dianbo Liu. Structure agnostic federated learning by adaptable gradient descent. [PDF]
Sekou Remy and Oliver Bent. LEARNING TO ACT: NOVEL INTEGRATION OF ALGORITHMS AND MODELS FOR EPIDEMIC PREPAREDNESS. [PDF]
Diyuan Lu, Gerhard Kurz, Nenad Polomac, Iskra Gacheva, Elke Hattingen and Jochen Triesch. Multiple Instance-Based Tumor Detection from Magnetic Resonance Spectroscopy Data. [PDF]
Hannes Stärk, Christian Dallago, Michael Heinzinger and Burkhard Rost. Light Attention Predicts Protein Location from the Language of Life. [PDF]
Alessandro Maria Selvitella and Kathleen Lois Foster. Bayesian detection and uncertainty quantification of the first change point of the COVID-19 case curve in the Midwest: Timeliness of non-pharmaceutical interventions.. [PDF]