no code implementations • 30 Aug 2021 • Mohammad Amin Morid, Olivia R. Liu Sheng, Joseph Dunbar
Second, these methods depend on feature engineering to capture the sequential nature of patient data, which may not adequately leverage the temporal patterns of the medical events and their dependencies.
no code implementations • 14 Sep 2020 • Mohammad Amin Morid, Olivia R. Liu Sheng, Kensaku Kawamoto, Samir AbdelRahman
Temporal patterns learned from medical, visit and cost data made significant contributions to the prediction performance.
no code implementations • 14 Sep 2020 • Mohammad Amin Morid, Olivia R. Liu Sheng, Kensaku Kawamoto, Travis Ault, Josette Dorius, Samir AbdelRahman
To prepare the data for modeling and prediction, the time series data of cost, visit and medical information were extracted in the form of fine-grain features (i. e., segmenting each time series into a sequence of consecutive windows and representing each window by various statistics such as sum).
no code implementations • 27 Apr 2020 • Mohammad Amin Morid, Alireza Borjali, Guilherme Del Fiol
Inception models were the most commonly used in breast related studies (50%), while VGGNet was the common in eye (44%), skin (50%) and tooth (57%) studies.
no code implementations • 25 Apr 2017 • Mohammad Amin Morid, Olivia R. Liu Sheng, Samir AbdelRahman
This study makes contributions to time series classification and early ICU mortality prediction via identifying and enhancing temporal feature engineering and reduction methods for similarity-based time series classification.
no code implementations • 25 Apr 2017 • Mohammad Amin Morid, Olivia R. Liu Sheng, Samir AbdelRahman
The first component captures dynamic changes of patients status in the ICU using their time series data (e. g., vital signs and laboratory tests).