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Mar 23, 2023

Healthcare out of (human) touch?

By Marta Iraola | EURACTIV.com 07-06-2023 (updated:

By Marta Iraola | EURACTIV.com

07-06-2023 (updated: 07-06-2023 )

Editorial/Opinion An OpinionNewsArticle is a NewsArticle that primarily expresses opinions rather than journalistic reporting of news and events.

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While artificial intelligence (AI) in a healthcare setting can be a powerful tool, with machine learning enabling medical professionals to diagnose diseases, personalise treatments and develop new drugs, experts have urged for caution in its deployment.

Hans Danneels, CEO of Byteflies, a medical technology company that develops wearable health devices, told an event in Antwerp last week about his own experience of AI in healthcare when he had twins that needed monitoring in the hospital for nine days.

At the beginning of their stay, he explained, the twins needed nurse visits every few hours to monitor and make note of the babies’ vital signs. As the twins improved, the frequency of the visits decreased, but they stayed in the hospital.

This is where Byteflies comes into play. Danneels talked about the telemonitoring devices they develop and how they can help the patients.

"More and more, for very acute things, you will still go to the hospital, but this whole function, this monitoring will shift to the home," he said.

The idea is to simplify the monitoring work for healthcare professionals at the hospital by sending patients home with one of these devices keeping track of any changes.

He explained that the algorithm is very sensitive in order to not miss any relevant event.

"We have a human in the loop that sees and classifies the results", he explained.

The need for humans to be involved in any healthcare process dealing with AI was highlighted by Leonie de Best from Madam Therapeutics, a biotech company working to develop novel antimicrobial therapies.

She explained that it is extremely important to verify the results of data analysis made using AI because every algorithm has to be trained with data and these data sets can be biased.

De Best added that without having a curated and representative data set to analyse it is easier to misjudge the correctness of the models.

"You miss a lot, or you make really big mistakes. You put crap in you get crap out," she added.

Madam Therapeutics is using Artificial Intelligence to screen big amounts of antimicrobial peptides to create a safety profile.

Thanks to AI, her company is able to screen and analyse a hundred million randomly chosen antimicrobial peptides saving them a lot of time in the process of creating safety profiles.

"That is something that took a couple of months while otherwise, it would have taken years," she explained.

According to Carlo Boutton, AI tools cannot substitute a doctor in any case. "We should not underestimate the human brain, AI should not be a replacement but an add-on," he said.

"It is more like a stethoscope, a tool that helps doctors and nurses to really spend more time on the patient," added Byteflies’ Danneels.

There is a general agreement on the fact that in order to use these new tools in the correct way it is important to include people that understand the multidisciplinary aspect of the problem, not just the data.

Doctors are still essential in every process as they are the ones that know the background of the patient, talk to the caregivers and have a more holistic view.

Machine learning, as the examples given by the different stakeholders show, needs large datasets to analyse and reach useful results.

One of the problems companies often face is difficult access to the necessary information, especially when it comes to accessing patients’ data from hospitals or clinics.

Data sharing is a controversial topic among stakeholders, as they all recognised the need to have access to patients’ information, reactions to therapies and clinical trials, among others.

At the same time, as business companies, they are reluctant to give their clients’ data away.

Madam Therapeutics’ de Best explained the need for data to be as complete and comprehensive as possible in order to make studies truly representative.

For that, Danneels stressed the need for people to own their own data so they don't depend on big tech companies and their interests in the future.

As he told EURACTIV, he welcomes the European's Commission proposal for a European Health Data Space (EHDS) to harmonise all the data that already exists in the EU.

According to Danneels, it is the best solution also for companies so they don't need to work with 27 different frameworks and will be able to compare information between countries.

"There is a big risk, and it is not regulation itself but that is too slow," he said. "It is important to give oxygen to innovation and to companies to grow in a framework, that is aligned with how Europe looks at data."

– By Marta Iraola

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[Edited by Nathalie Weatherald]

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