Evaluation metrics for deep learning imputation models

O Boursalie, R Samavi, TE Doyle - International Workshop on Health …, 2021‏ - Springer
There is growing interest in imputing missing data in tabular datasets using deep learning. A
commonly used metric in evaluating the performance of a deep learning-based imputation …

Evaluation methodology for deep learning imputation models

O Boursalie, R Samavi… - Experimental Biology and …, 2022‏ - journals.sagepub.com
There is growing interest in imputing missing data in tabular datasets using deep learning.
Existing deep learning–based imputation models have been commonly evaluated using root …

Short‐Axis PET Image Quality Improvement by Attention CycleGAN Using Total‐Body PET

C Shang, G Zhao, Y Li, J Yuan, M Wang… - Journal of …, 2022‏ - Wiley Online Library
The quality of positron emission tomography (PET) imaging is positively correlated with
scanner sensitivity, which is closely related to the axial field of view (FOV). Conventional …

Evaluation of Sequential and Temporally Embedded Deep Learning Models for Health Outcome Prediction

O Boursalie, R Samavi, TE Doyle - Deep Learning Applications, Volume 4, 2022‏ - Springer
Deep learning sequential models are increasingly being used to predict patients' health
outcomes by analyzing their medical histories. In this paper, we investigate the design …

Evaluation methodology for deep learning imputation models

R Samavi, O Boursalie, TE Doyle‏ - rshare.library.torontomu.ca
There is growing interest in imputing missing data in tabular datasets using deep learning.
Existing deep learning–based imputation models have been commonly evaluated using root …

Temporally-Embedded Deep Learning Model for Health Outcome Prediction

O Boursalie - 2021‏ - macsphere.mcmaster.ca
Deep learning models are increasingly used to analyze health records to model disease
progression. Two characteristics of health records present challenges to developers of deep …