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Explainable Machine Learning for ICU Readmission Prediction
Readmission contributes to this pathway's difficulty, occurring when patients are admitted again to the ICU in a short timeframe, resulting in high mortality rates and high resource utilisation.
Improving Text-based Early Prediction by Distillation from Privileged Time-Series Text
In this study, we propose to treat this neglected text as privileged information available during training to enhance early prediction modeling through knowledge distillation, presented as Learning using Privileged tIme-sEries Text (LuPIET).
Quantifying machine learning-induced overdiagnosis in sepsis
The proliferation of early diagnostic technologies, including self-monitoring systems and wearables, coupled with the application of these technologies on large segments of healthy populations may significantly aggravate the problem of overdiagnosis.
A Survey on Deep Learning and Explainability for Automatic Report Generation from Medical Images
Every year physicians face an increasing demand of image-based diagnosis from patients, a problem that can be addressed with recent artificial intelligence methods.
Statistical Section Segmentation in Free-Text Clinical Records
Automatically segmenting and classifying clinical free text into sections is an important first step to automatic information retrieval, information extraction and data mining tasks, as it helps to ground the significance of the text within.
