15 citations · 21 across the 11 of their papers we have counts for
5 papers · 1 filter
Counterfactual Explanations for Time Series Forecasting
Zhendong Wang, Ioanna Miliou, Isak Samsten +1
Among recent developments in time series forecasting methods, deep forecasting models have gained popularity as they can utilize hidden feature patterns in time series to improve f…
FLICU: A Federated Learning Workflow for Intensive Care Unit Mortality Prediction
Lena Mondrejevski, Ioanna Miliou, Annaclaudia Montanino +3
Although Machine Learning (ML) can be seen as a promising tool to improve clinical decision-making for supporting the improvement of medication plans, clinical procedures, diagnose…
Robust Explanations for Private Support Vector Machines
Rami Mochaourab, Sugandh Sinha, Stanley Greenstein +1
We consider counterfactual explanations for private support vector machines (SVM), where the privacy mechanism that publicly releases the classifier guarantees differential privacy…
Aggregate-Eliminate-Predict: Detecting Adverse Drug Events from Heterogeneous Electronic Health Records
Maria Bampa, Panagiotis Papapetrou
We study the problem of detecting adverse drug events in electronic healthcare records. The challenge in this work is to aggregate heterogeneous data types involving diagnosis code…
Explainable time series tweaking via irreversible and reversible temporal transformations
Isak Karlsson, Jonathan Rebane, Panagiotis Papapetrou +1
Time series classification has received great attention over the past decade with a wide range of methods focusing on predictive performance by exploiting various types of temporal…