Hakima Laribi
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View article: Synthetic Data for Accessible Learning in Healthcare: Improving Mortality Prediction with Longitudinal Data
Synthetic Data for Accessible Learning in Healthcare: Improving Mortality Prediction with Longitudinal Data Open
Accurate prediction of medium-term survival after admission is necessary for identifying end-of-life patients who may benefit from earlier goals of care (GOC) discussions. While previous studies have leveraged admission data from electroni…
View article: Leveraging patients’ longitudinal data to improve the Hospital One-year Mortality Risk
Leveraging patients’ longitudinal data to improve the Hospital One-year Mortality Risk Open
Purpose Predicting medium-term survival after admission is necessary for identifying end-of-life patients who may benefit from goals of care (GOC) discussions. Considering that several patients have multiple hospital admissions, this study…
View article: Machine learning strategies to predict late adverse effects in childhood acute lymphoblastic leukemia survivors
Machine learning strategies to predict late adverse effects in childhood acute lymphoblastic leukemia survivors Open
Acute lymphoblastic leukemia is the most frequent pediatric cancer. Approximately two third of survivors develop one or more health complications known as late adverse effects following their treatments. The existing measures offered to pa…