9 citations · 26 across the 11 of their papers we have counts for
6 papers · 1 filter
Attention-based Multi-task Learning for Base Editor Outcome Prediction
Amina Mollaysa, Ahmed Allam, Michael Krauthammer
Human genetic diseases often arise from point mutations, emphasizing the critical need for precise genome editing techniques. Among these, base editing stands out as it allows targ…
Simple Contrastive Representation Learning for Time Series Forecasting
Xiaochen Zheng, Xingyu Chen, Manuel Schürch +3
Contrastive learning methods have shown an impressive ability to learn meaningful representations for image or time series classification. However, these methods are less effective…
Exploratory Analysis of Federated Learning Methods with Differential Privacy on MIMIC-III
Aron N. Horvath, Matteo Berchier, Farhad Nooralahzadeh +2
Background: Federated learning methods offer the possibility of training machine learning models on privacy-sensitive data sets, which cannot be easily shared. Multiple regulations…
Patient Similarity Analysis with Longitudinal Health Data
Ahmed Allam, Matthias Dittberner, Anna Sintsova +2
Healthcare professionals have long envisioned using the enormous processing powers of computers to discover new facts and medical knowledge locked inside electronic health records.…
AutoDiscern: Rating the Quality of Online Health Information with Hierarchical Encoder Attention-based Neural Networks
Laura Kinkead, Ahmed Allam, Michael Krauthammer
Patients increasingly turn to search engines and online content before, or in place of, talking with a health professional. Low quality health information, which is common on the i…
Neural networks versus Logistic regression for 30 days all-cause readmission prediction
Ahmed Allam, Mate Nagy, George Thoma +1
Heart failure (HF) is one of the leading causes of hospital admissions in the US. Readmission within 30 days after a HF hospitalization is both a recognized indicator for disease p…