Artificial intelligence in the medical field
In the third episode of the “Ganado Meets Tech” podcast, Ganado Advocates’ IP/TMT partner Paul Micallef Grimaud met a medical consultant in nuclear medicine Andre Mallialecturer in artificial intelligence at the University of Malta Alexei Dingli and entrepreneur and lawyer Gege Gatt to examine how AI is positively impacting the healthcare industry and providing us with unprecedented levels of healing and health management, while discussing the legal and ethical risks involved.
Looking through the lens of a nuclear medicine physician whose profession revolves around the interpretation of medical images, Andrew Mallia opines that, if used with caution, artificial intelligence (AI) and, in particular, deep learning and computer vision technology, can lead to the desired level of precision medicine.
As explained by Mallia and further developed by Alexiei Dingli, this science drives technology to highlight details in medical images that require further investigation and analysis by the medical professional, thereby reducing time and allowing greater precision in the interpretation of the images.
This science is based on acquired intelligence of the machine, which it derives from “studying” large amounts of images which it then processes internally to be able to form its understanding of what a “normal” image is. ” and an “abnormal” image. and requires investigation.
Mallia explains that it has been shown through studies that machines can perform these limited tasks better than humans.
According to Gege Gatt, this could be explained by the very fact that human decisions are often impacted by the personal circumstances in which the individual who makes the decision finds himself. This was demonstrated, for example, in a study conducted in the United States of judges deciding parole cases, where it was found that decisions were very often influenced by judges’ subjective opinions, their personal mood and other extraneous circumstances.
Interestingly, however, humans still instinctively trust other humans more than machines that perform their tasks objectively. That said, participants all agreed that transparency in the machine’s decision-making process is key to building trust in technology, and it’s no surprise there’s more emphasis on glass boxes (a system in which the decision-making process of the machine can be followed), rather than black boxes (a system in which the output of the machine is not explainable).
While AI and technology is a valuable tool…the need for human interaction. and health professionals will not diminish
With the medical sector being so essential to society, one can only expect the legal and regulatory framework to be rather intense. This brings together privacy rights under the GDPR, the European Convention on Human Rights and the EU Charter of Fundamental Rights, which require patients to be told very clearly what use is to be made. be made of their data and that they have the right to freely access and expressly consent to their health data being used in this way. It is also prohibited, except with the free, informed and express consent of the patient, for fully automated decisions to be made based on the patient’s health data.
Similarly, patient rights charters insist that patients be fully informed about care solutions related to their care and recovery, while the European Commission’s draft regulation on AI classifies l use of AI in the medical sphere, especially where diagnosis and cure is concerned, as high risk, requiring high levels of certification by independent auditors regulated by national regulatory authorities in accordance with requirements which will be harmonized across Europe once the regulation is adopted.
The interplay between product liability and medical malpractice is particularly interesting, as Mallia mentioned, and will almost certainly be tested in court in the near future.
Despite this intense legal framework, which some might criticize as slowing the pace of development, being aware of and respectful of privacy rights when developing technology solutions leads to higher levels of trust and widespread adoption of solutions.
Gatt experienced this in discussions he had with the NHS. He and his team at EBO.ai, a company that provides AI solutions for patient management to the NHS, navigated the various legal and regulatory milestones during a two-year journey. But, beyond passing legal and regulatory testing, what inspired trust and ultimately acceptance of their product was the ability to demonstrate that ethical considerations ran through the development stages with the result that the solution technology meets human-centered goals, including inclusiveness, augmenting (not replacing) human judgment, privacy, and patient empowerment.
Mallia is confident that while AI and technology is a valuable tool that will continue to make a marked difference in the way we receive medical treatment, the need for human interaction and healthcare professionals will not diminish.
In addition to medico-legal frameworks that require medical care to be provided only by licensed medical professionals (an AI system cannot be considered as such), the medical professional is interested in holistic healing and well-being of the patient, as opposed to a machine which is trained to perform one or a defined set of tasks.
Ultimately, Mallia agrees with Stanford’s Curtis Langlotz, who said, “AI will not replace radiologists, but radiologists who use AI will replace radiologists who don’t.”
The opportunities offered by technology, and AI in particular, are endless, as demonstrated by Dingli, who is currently working on a groundbreaking project that aims to alleviate pain through AI and reality-induced ‘distraction’. which leads the patient to “forget” the pain.
Ultimately, in Gatt’s words, technological solutions should always be designed with human well-being at the very center and in a way that fully respects the values of humanity. Only then could technology serve humanity and truly make a positive difference in our lives.
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