Explainable artificial intelligence is increasingly used in machine learning (ML) based decision-making systems in healthcare. However, little research has compared the utility of different explanation methods in guiding healthcare experts for …
Recent advancements in Natural Language Processing (NLP) using large pre-trained neural language models were recently used in various downstream tasks, such as text generation. In primary healthcare, such systems can generate very short summaries of …
The recent development and successful deployment of large pre-trained natural language models in few-shot and zero-shot scenarios enabled impressive results in different downstream tasks. One such task is abstractive text summarization combining …
To make predictions and explore large datasets, healthcare is increasingly applying advanced algorithms of artificial intelligence. However, to make well-considered and trustworthy decisions, healthcare professionals require ways to gain insights in …
At the time of the outbreak of the coronavirus pandemic, several measures were in place to limit the spread of the virus, such as lockdown and restriction of social contacts. Many colleges thus had to shift their education from personal to online …
Background: Health recommender systems (HRSs) offer the potential to motivate and engage users to change their behavior by sharing better choices and actionable knowledge based on observed user behavior. Objective: We aim to review HRSs targeting …
There is a need of ensuring machine learning models that are interpretable. Higher interpretability of the model means easier comprehension and explanation of future predictions for end-users. Further, interpretable machine learning models allow …