Tell me about your role with IEEE
I am a technical advisor, covering topics such as information systems, AI, and robotics in the press for IEEE. I have written many articles and have taken part in numerous interviews.
How is AI transforming the healthcare sector during the ongoing pandemic and what role does robotics play in this?
We saw different technical approaches. Firstly, it is possible to use telecare and innovative methods for triage patients. Additionally, there are examples of videoconferencing, or the use of chatbots, that have been used to guide patients to the right care. At the same time, we have seen the potential for robots to help disinfect areas in hospital settings, train stations, airports, and even hotels.
What are the core benefits of utilising this technology for virus management?
We are talking about scalability and cost-effective solutions for the global pandemic. So, on one hand, there will be a shortage of care professionals such as medical doctors, nurses, and assistants. In most scenarios, some of these individuals were infected themselves and had to be isolated.
By decentralising the need to be present in hospitals and care centres by using videoconferencing technologies, some care professionals can still work remotely. On another spectrum, we have the potential and existing COVID-19 patients, who in certain scenarios, were not required to go physically to a hospital to be consulted.
We have seen a tremendous overload in terms of care settings, and rationalising care has become so important. Certain patients are able to receive care instructions through videoconferencing which saves time, effort, and costs. Finally, we have seen the use of information systems to disseminate information and keep track of vaccination certificates, which has been crucial.
Looking specifically at diagnosis, how can AI support healthcare workers?
Yes. Through technological platforms such as cloud systems in the form of surveys, where people can answer a certain number of questions. The system can then use machine learning techniques to infer likely outcomes with a certain degree of confidence. An example of this could be showing an individual is infected, or that there is a high probability that they will suffer from a disease in the future.
Outside of the pandemic, how can AI transform healthcare as a whole with image recognition and NLP?
Essentially, we are talking about the application of machine learning techniques for image recognition and speech recognition. Image recognition is already used in a wide spectrum of scenarios such as cancer detection. For example, computers can be loaded with real-time patient images to identify with high precision a specific tumour region.
“In the coming decades, we could expect significant advances and application of these techniques, as they prove to be crucial in medical diagnosis. When it comes to NLP, perhaps the most important application would be speech recognition for chatbots and robots to better understand human language. There is an immense set of applications where one could imagine a virtual agent asking questions to a patient or a patient talking to a machine for triggering certain functionalities and requests.