5 papers
Ensemble of Unsupervised Deep Learning for Clustering Imbalanced Tabular Data
Pulock Das, Yina Hou, Md. Kamrozzaman Bhuiyan +1
Data imbalance poses a major challenge in supervised classification, where the majority-class bias contributes to false negatives and overestimates classification accuracy. Unsuper…
Mining Electronic Health Records to Investigate Effectiveness of Ensemble Deep Clustering
Manar D. Samad, Yina Hou, Shrabani Ghosh
In electronic health records (EHRs), clustering patients and distinguishing disease subtypes are key tasks to elucidate pathophysiology and aid clinical decision-making. However, c…
Vine Copulas for Analyzing Multivariate Conditional Dependencies in Electronic Health Records Data
Manar D. Samad, Yina Hou, Megan A. Witherow +1
Electronic health records (EHR) store hundreds of demographic and laboratory variables from large patient populations. Traditional statistical methods have limited capacity in proc…
Causal Explainability of Machine Learning in Heart Failure Prediction from Electronic Health Records
Yina Hou, Shourav B. Rabbani, Liang Hong +2
The importance of clinical variables in the prognosis of the disease is explained using statistical correlation or machine learning (ML). However, the predictive importance of thes…
DeepIFSAC: Deep Imputation of Missing Values Using Feature and Sample Attention within Contrastive Framework
Ibna Kowsar, Shourav B. Rabbani, Yina Hou +1
Missing values of varying patterns and rates in real-world tabular data pose a significant challenge in developing reliable data-driven models. The most commonly used statistical a…