Zobrazeno 1 - 10
of 320
pro vyhledávání: '"Canoy Dexter"'
Autor:
Li, Yikuan, Mamouei, Mohammad, Rao, Shishir, Hassaine, Abdelaali, Canoy, Dexter, Lukasiewicz, Thomas, Rahimi, Kazem, Salimi-Khorshidi, Gholamreza
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 health systems' ability to employ ML models in clinical decision-maki
Externí odkaz:
http://arxiv.org/abs/2205.07234
Autor:
Rao, Shishir, Mamouei, Mohammad, Salimi-Khorshidi, Gholamreza, Li, Yikuan, Ramakrishnan, Rema, Hassaine, Abdelaali, Canoy, Dexter, Rahimi, Kazem
Observational causal inference is useful for decision making in medicine when randomized clinical trials (RCT) are infeasible or non generalizable. However, traditional approaches fail to deliver unconfounded causal conclusions in practice. The rise
Externí odkaz:
http://arxiv.org/abs/2202.03487
Autor:
Solares, Jose Roberto Ayala, Zhu, Yajie, Hassaine, Abdelaali, Rao, Shishir, Li, Yikuan, Mamouei, Mohammad, Canoy, Dexter, Rahimi, Kazem, Salimi-Khorshidi, Gholamreza
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 transfer learning: Exploiting commonalities between different learning t
Externí odkaz:
http://arxiv.org/abs/2107.12919
Autor:
Li, Yikuan, Mamouei, Mohammad, Salimi-Khorshidi, Gholamreza, Rao, Shishir, Hassaine, Abdelaali, Canoy, Dexter, Lukasiewicz, Thomas, Rahimi, Kazem
Electronic health records represent a holistic overview of patients' trajectories. Their increasing availability has fueled new hopes to leverage them and develop accurate risk prediction models for a wide range of diseases. Given the complex interre
Externí odkaz:
http://arxiv.org/abs/2106.11360
Autor:
Li, Yikuan, Rao, Shishir, Mamouei, Mohammad, Salimi-Khorshidi, Gholamreza, Canoy, Dexter, Hassaine, Abdelaali, Lukasiewicz, Thomas, Rahimi, Kazem
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 to their statistical counterparts. While this provides an important op
Externí odkaz:
http://arxiv.org/abs/2102.12936
Autor:
Rao, Shishir, Li, Yikuan, Ramakrishnan, Rema, Hassaine, Abdelaali, Canoy, Dexter, Cleland, John, Lukasiewicz, Thomas, Salimi-Khorshidi, Gholamreza, Rahimi, Kazem
Predicting the incidence of complex chronic conditions such as heart failure is challenging. Deep learning models applied to rich electronic health records may improve prediction but remain unexplainable hampering their wider use in medical practice.
Externí odkaz:
http://arxiv.org/abs/2101.11359
Autor:
Li, Yikuan, Rao, Shishir, Hassaine, Abdelaali, Ramakrishnan, Rema, Zhu, Yajie, Canoy, Dexter, Salimi-Khorshidi, Gholamreza, Lukasiewicz, Thomas, Rahimi, Kazem
One major impediment to the wider use of deep learning for clinical decision making is the difficulty of assigning a level of confidence to model predictions. Currently, deep Bayesian neural networks and sparse Gaussian processes are the main two sca
Externí odkaz:
http://arxiv.org/abs/2003.10170
Publikováno v:
BMC Medical Research Methodology, Vol 12, Iss 1, p 161 (2012)
Abstract Background Electronic linkage to routine administrative datasets, such as the Hospital Episode Statistics (HES) in England, is increasingly used in medical research. Relatively little is known about the reliability of HES diagnostic informat
Externí odkaz:
https://doaj.org/article/28206e7cdc224623aa395100c2e375ea
Autor:
Li, Yikuan, Rao, Shishir, Solares, Jose Roberto Ayala, Hassaine, Abdelaali, Canoy, Dexter, Zhu, Yajie, Rahimi, Kazem, Salimi-Khorshidi, Gholamreza
Today, despite decades of developments in medicine and the growing interest in precision healthcare, vast majority of diagnoses happen once patients begin to show noticeable signs of illness. Early indication and detection of diseases, however, can p
Externí odkaz:
http://arxiv.org/abs/1907.09538
Autor:
Hassaine, Abdelaali, Canoy, Dexter, Solares, Jose Roberto Ayala, Zhu, Yajie, Rao, Shishir, Li, Yikuan, Zottoli, Mariagrazia, Rahimi, Kazem, Salimi-Khorshidi, Gholamreza
Multimorbidity, or the presence of several medical conditions in the same individual, has been increasing in the population, both in absolute and relative terms. However, multimorbidity remains poorly understood, and the evidence from existing resear
Externí odkaz:
http://arxiv.org/abs/1907.08577