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Interaction between AI and patient

In order to benefit from AI, patients need the support of healthcare providers and institutions.
Someone looking at his smartwatch
© Ketut Subiyanto via Pexels.

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 and actions.

AI in healthcare can offer patients more control over their health and wellbeing, reducing the need for assistance or hospitalization. Home monitoring systems help people to stay well by encouraging healthy behaviours and providing care remotely. For instance, smartwatches, while not designed as medical devices, display a range of applications such as vital sign monitoring. Activity trackers that gather medical data allow patients to assess a need for observation or support if the collected values fall outside the conventional range.

Moreover, approved medical devices like smart insulin pens or connected inhalers and their associated apps are smart technologies, successfully put within the hands of the everyday consumer, providing daily guidance, and allowing them to oversee their own health needs.

Educating patients in AI allows them to develop self-awareness and gain better control over decisions affecting their health. This is a critical process required to enhance AI safety standards and to make them more equitable, robust, and thus more reliable for patients.

Indeed, healthcare transition toward artificial intelligence-reliant standards depends on patient trust and acknowledgment of such models. While patient consent is an essential precondition for the successful implementation of AI in health care, patients’ access, understanding, and response to AI outcomes at various steps of their journey may have tremendous consequences on their healing. For example, in 2015, an application designed to predict which patients might develop complications because of pneumonia made critical errors placing high-risk asthmatic patients in the low-risk category and proposing to send them home (Caruana et. al, 2015).

When patient-AI interactions are involved, AI developers must ensure that healthcare professionals are directly involved in quality control and approvals of these systems. A poor use of AI technology exposes patients to the risk of biased and erroneous predictions. For that reason, healthcare professionals should actively strive to improve patients’ literacy and guide them in their learning and perception of AI predictions and decisions. The application of AI in healthcare needs to be transparent and regulated to protect patients’ interests when it comes to ethical standards.

© AIProHealth Project
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How Artificial Intelligence Can Support Healthcare

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