Research — Decorte Future Industries

While all our IP is owned by the company and all research happens in-house, current and former team members have published widely in public peer-reviewed journals on underlying principles and adjacent fields as part of previous or ongoing academic careers. Below are some papers previously published or co-published by current or former Decorte Future Industries team members, as part of their membership of various research groups or during doctoral research, exploring and validating various methods of health data gathering using audio.

'“Embracing the Imaginary: Deep Complex-valued Networks for Heart Murmur Detection,” 2023, Computing in Cardiology (Cinc) 50, 1-4

Authors: Erika Bondareva, Georgios Rizos, Jing Han, Cecilia Mascolo.

“Modified Variable Kernel Length ResNets for Heart Murmur Detection and Clinical Outcome Prediction using Multi-positional Phonocardiogram Recording”, 2022, PhysioNet Challenge.

Authors: Vijay Vignesh Venkataramani, Akshit Garg, U. Deva Priyakumar

“Towards Uncertainty-Aware Murmur Detection in Heart Sounds via Tandem Learning”, 2022 Computing in Cardiology (CinC) 498, 1-4

Authors: Erika Bondareva; Tong Xia; Jing Han; Cecilia Mascolo

“Modern AI/ML Methods for Healthcare: Opportunities and Challenges”, 2022, Distributed Computing and Intelligent Technology, 18th International Conference

Authors: Akshit Garg, Vijay Vignesh Venkataramani, Akshaya Karthikeyan, U. Deva Priyakumar

“Exploring longitudinal cough, breath, and voice data for COVID-19 progression prediction via sequential deep learning: model development and validation”, Journal of medical Internet research 24 (6), e37004

Authors: Ting Dang, Jing Han, Tong Xia, Dimitris Spathis, Erika Bondareva, Chloë Siegele-Brown, Jagmohan Chauhan, Andreas Grammenos, Apinan Hasthanasombat, R Andres Floto, Pietro Cicuta, Cecilia Mascolo.

“Stress Inference from Abdominal Sounds using Machine Learning”, 2022, arXiv:2201.01232

Authors: Erika Bondareva, Marios Constantinides, Michael S Eggleston, Ireneusz Jabłoński, Cecilia Mascolo, Zoran Radivojevic, Sanja Šćepanović.

“Segmentation-free Heart Pathology Detection Using Deep Learning”, 2021, 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology

Authors: Erika Bondareva, Jing Han, William Bradlow, Cecilia Mascolo.

“Sounds of COVID-19: exploring realistic performance of audio-based digital testing”, 2022, Nature Partner Journal Digital Medicine 5, 1-9.

Authors: Jing Han, Tong Xia, Dimitris Spathis, Erika Bondareva, Chloë Brown, Jagmohan Chauhan, Ting Dang, Andreas Grammenos, Apinan Hasthanasombat, Andres Floto, Pietro Cicuta & Cecilia Mascolo.

“COVID-19 Sounds: A Large-Scale Audio Dataset for Digital Respiratory Screening”, 2021, 35th Conference on Neural Information Processing Systems and Datasets and Benchmarks Track

Authors: Tong Xia, Dimitris Spathis, J Ch, Andreas Grammenos, Jing Han, Apinan Hasthanasombat, Erika Bondareva, Ting Dang, Andres Floto, Pietro Cicuta, Cecilia Mascolo.