13 citations · 20 across the 6 of their papers we have counts for
6 papers
Quantum Multiple Kernel Learning in Financial Classification Tasks
Shungo Miyabe, Brian Quanz, Noriaki Shimada +11
Financial services is a prospect industry where unlocked near-term quantum utility could yield profitable potential, and, in particular, quantum machine learning algorithms could p…
Clinical outcome prediction under hypothetical interventions -- a representation learning framework for counterfactual reasoning
Yikuan Li, Mohammad Mamouei, Shishir Rao +5
Most machine learning (ML) models are developed for prediction only; offering no option for causal interpretation of their predictions or parameters/properties. This can hamper the…
Targeted-BEHRT: Deep learning for observational causal inference on longitudinal electronic health records
Shishir Rao, Mohammad Mamouei, Gholamreza Salimi-Khorshidi +5
Observational causal inference is useful for decision making in medicine when randomized clinical trials (RCT) are infeasible or non generalizable. However, traditional approaches…
Transfer Learning in Electronic Health Records through Clinical Concept Embedding
Jose Roberto Ayala Solares, Yajie Zhu, Abdelaali Hassaine +6
Deep learning models have shown tremendous potential in learning representations, which are able to capture some key properties of the data. This makes them great candidates for tr…
Hi-BEHRT: Hierarchical Transformer-based model for accurate prediction of clinical events using multimodal longitudinal electronic health records
Yikuan Li, Mohammad Mamouei, Gholamreza Salimi-Khorshidi +5
Electronic health records represent a holistic overview of patients' trajectories. Their increasing availability has fueled new hopes to leverage them and develop accurate risk pre…
Risk factor identification for incident heart failure using neural network distillation and variable selection
Yikuan Li, Shishir Rao, Mohammad Mamouei +5
Recent evidence shows that deep learning models trained on electronic health records from millions of patients can deliver substantially more accurate predictions of risk compared…