no code implementations • 11 Dec 2023 • Will E. Thompson, David M. Vidmar, Jessica K. De Freitas, John M. Pfeifer, Brandon K. Fornwalt, Ruijun Chen, Gabriel Altay, Kabir Manghnani, Andrew C. Nelsen, Kellie Morland, Martin C. Stumpe, Riccardo Miotto
Identifying disease phenotypes from electronic health records (EHRs) is critical for numerous secondary uses.
no code implementations • 12 Apr 2021 • Martha Dais Ferreira, Michal Malyska, Nicola Sahar, Riccardo Miotto, Fernando Paulovich, Evangelos Milios
Machine Learning (ML) is widely used to automatically extract meaningful information from Electronic Health Records (EHR) to support operational, clinical, and financial decision-making.
no code implementations • 11 Jan 2021 • Tingyi Wanyan, Hossein Honarvar, Suraj K. Jaladanki, Chengxi Zang, Nidhi Naik, Sulaiman Somani, Jessica K. De Freitas, Ishan Paranjpe, Akhil Vaid, Riccardo Miotto, Girish N. Nadkarni, Marinka Zitnik, ArifulAzad, Fei Wang, Ying Ding, Benjamin S. Glicksberg
This has been a major issue for developing ML models for the coronavirus-disease 2019 (COVID-19) pandemic where data is highly imbalanced, particularly within electronic health records (EHR) research.
1 code implementation • 14 Mar 2020 • Isotta Landi, Benjamin S. Glicksberg, Hao-Chih Lee, Sarah Cherng, Giulia Landi, Matteo Danieletto, Joel T. Dudley, Cesare Furlanello, Riccardo Miotto
With these results, we demonstrate that ConvAE can generate patient representations that lead to clinically meaningful insights.
1 code implementation • 31 Oct 2019 • Hao-Chih Lee, Matteo Danieletto, Riccardo Miotto, Sarah T. Cherng, Joel T. Dudley
Constructing gene regulatory networks is a critical step in revealing disease mechanisms from transcriptomic data.
1 code implementation • 1 Oct 2019 • Hao-Chih Lee, Sarah T. Cherng, Riccardo Miotto, Joel T. Dudley
Such requirements are particularly challenging for high-throughput imaging, where researchers must make decisions related to the trade-off between imaging quality and speed.
no code implementations • 15 Aug 2019 • Seyedmostafa Sheikhalishahi, Riccardo Miotto, Joel T. Dudley, Alberto Lavelli, Fabio Rinaldi, Venet Osmani
There is a notable use of relatively simple methods, such as shallow classifiers (or combination with rule-based methods), due to the interpretability of predictions, which still represents a significant issue for more complex methods.