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Found 6 papers, 3 papers with code
Using Bottleneck Adapters to Identify Cancer in Clinical Notes under Low-Resource Constraints
Processing information locked within clinical health records is a challenging task that remains an active area of research in biomedical NLP.
Nowruz at SemEval-2022 Task 7: Tackling Cloze Tests with Transformers and Ordinal Regression
This paper outlines the system using which team Nowruz participated in SemEval 2022 Task 7 Identifying Plausible Clarifications of Implicit and Underspecified Phrases for both subtasks A and B.
Assessing the risk of re-identification arising from an attack on anonymised data
The objective of this work is to calculate the risk of re-identification arising from a malicious attack to an anonymised dataset, as described below.
Privacy-aware Early Detection of COVID-19 through Adversarial Training
One of our main contributions is that we specifically target the development of effective COVID-19 detection models with built-in mechanisms in order to selectively protect sensitive attributes against adversarial attacks.
Let Your Heart Speak in its Mother Tongue: Multilingual Captioning of Cardiac Signals
Cardiac signals, such as the electrocardiogram, convey a significant amount of information about the health status of a patient which is typically summarized by a clinician in the form of a clinical report, a cumbersome process that is prone to errors.
Student-Teacher Curriculum Learning via Reinforcement Learning: Predicting Hospital Inpatient Admission Location
Accurate and reliable prediction of hospital admission location is important due to resource-constraints and space availability in a clinical setting, particularly when dealing with patients who come from the emergency department.
