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Making a choice

In this video Lisa explains the reasoning behind the choice for the best AI solution for her department. Do you agree, or would you have chosen a different option? What …

Experts on the workforce replacement

In the previous step, you already reflected upon the potential workforce replacement. We also wanted to learn the opinion of patients, industry representatives, and healthcare professionals themselves on whether they …

Can we trust AI?

Now that we have learned more about the ethical and social aspects of artificial intelligence in healthcare, it would be interesting to reconsider the topic of the trustworthiness of artificial …

Challenges in AI-patient interaction

As healthcare is transitioning towards AI-reliant models, direct interactions between patients and AI will also increase. We asked people in the field to explain what challenges arise in this patient-AI …

Interaction between AI and patient

AI can be used to empower patients by enhancing their ability to make evidence-based health decisions. In this way, patients and medical practitioners become equal allies for responsible medical decisions …

General Data Protection Regulation (GDPR)

To learn more about the General Data Protection Regulation (GDPR), we have turned to legal expert Jeanne Mifsud-Bonnici. Jeanne is a Professor in European Technology Law and Human Rights at …

AI as a medical device

Increasingly, more products and services that use AI are being developed and marketed in the healthcare domain. Examples include radiology software that assists the radiologist in the detection of tumors, …

Acceptance of AI

Explainable AI gives access to why and how every input shapes a particular outcome provided by the AI, making it easier to understand the results. It allows healthcare professionals and …

What is explainable AI?

AI technologies are a powerful tool to face the rising labor shortage of healthcare and give professional workers tools to do their jobs in better conditions. They are an integrated …

Dealing with bias in AI

Bias is a phenomenon that occurs when the machine learning model systemically produces prejudiced results. It can be caused by bad quality or wrong example data, which is called representational …

Bias in AI

One of the seven requirements for reaching trustworthy AI is the application of diversity, non-discrimination, and fairness. In order to meet this requirement, bias should be avoided. In this video, …