Peta Rolls grew accustomed to getting the AI's regular check-in each morning.
A routine morning call by an automated voice assistant was not part of the care package Rolls envisioned when she signed up for the in-home support but when she was invited to be part of the pilot program four months ago, the elderly lady agreed because she wished to contribute. Even though, truth be told, her expectations weren't high.
Nevertheless, when she got the call, she says: “I was amazed by how interactive she was. It was remarkable for a machine.”
“She’d always ask ‘how are you feeling today?’ and that provides a chance if you’re feeling sick to say you felt sick, or I just say ‘I’m fine, thank you’.”
“The AI would then pose follow-up questions – ‘did you manage to go outdoors today?’”
The virtual assistant would also inquire about what the user was planning for the day and “it would reply appropriately.”
“When I mentioned I plan to go shopping, it would ask are you shopping for clothes or groceries? It was quite engaging.”
Bots Easing the Administrative Burden on Healthcare Staff
The trial, which has now wrapped up its initial stage, is an example in which advances in AI technology are being taken up in healthcare.
Health tech firm the provider partnered with St Vincent’s regarding the program to use its generative AI technology to provide social interaction, as well as an opportunity for elderly recipients to report any medical concerns or issues for a caregiver to address.
Dean Jones, head of St Vincent’s At Home, says the AI check-in being trialled does not replace any in-person visits.
“Clients still receive a weekly face to face meeting, but between these meetings … the [AI] system allows a routine call, which can then escalate any potential concerns to either our team or a client’s family,” the director says.
The managing director, the managing director of the company, reports there haven’t been any adverse incidents reported from the pilot program.
Healthily uses advanced AI “with very clear guardrails and prompts” to ensure the conversation is secure and mechanisms are established to respond to serious health issues promptly, the director states. As an instance, if a patient is reporting heart symptoms, it would be alerted to the care team and the call terminated so the individual could call emergency services.
She believes AI has an significant part given significant workforce challenges throughout the medical industry.
“The benefit securely, with technology like this, is reduce the admin burden on the staff so qualified health professionals can focus on performing the duties that they’re trained to do,” she comments.
AI Not as New as Often Believed
An expert, the co-founder of the national AI health alliance, says older forms of AI have been a common feature of healthcare for a long time, often in “administrative functions” such as analyzing scans, cardiograms and lab reports.
“Any computer program that carries out a function that requires judgment in some way is artificial intelligence, irrespective of how it accomplishes it,” states the professor, who is additionally the head of the Centre for Health Informatics at Macquarie University.
“When visiting the radiology unit, medical imaging center or pathology lab, you’ll see software in machines doing just that.”
Over the past decade, advanced versions of artificial intelligence known as “machine learning” – a neural network method that allows algorithms to learn from extensive datasets – have been employed to interpret medical imaging and enhance detection, Coiera notes.
In November, a screening service became Australia’s first public health initiative to introduce machine reading technology to assist specialists in interpreting a select range of breast scans.
They are advanced systems that continue to need a qualified physician to evaluate the diagnosis they might suggest, and the responsibility for a medical decision sits with the healthcare provider, the professor says.
AI’s Role in Early Disease Detection
A research center in the city has been working alongside researchers from UCL London who pioneered artificial intelligence techniques to detect epilepsy brain abnormalities called specific brain malformations from brain scans.
These lesions trigger epileptic episodes that often are resistant with drugs, meaning surgery to remove them becomes the sole option. However, the surgery can only be performed if the surgeons can locate the abnormal tissue.
A study recently released in the scientific publication, a group from the research body, led by neurologist the lead researcher, demonstrated their “neural network tool” could detect the abnormalities in up to 94% of cases from MRI and PET scans in a subtype of the lesions that have historically been missed in more than half of patients (60%).
The system was developed using the scans of a group of individuals and then evaluated with pediatric cases and 12 adults. Of the 17 children, twelve underwent operations and eleven became free of seizures.
The tool employs AI algorithms similar to the mammography analysis – highlighting regions of abnormality, which are still checked by experts “speeding up the process to reach a conclusion,” Macdonald-Laurs explains.
She emphasises the team are still in the “early phases” of the work, with a additional research necessary to get the technology toward clinical implementation.
Prof Mark Cook, a brain specialist who was not involved in the study, notes MRI scans now generate such huge amounts of high-resolution data that it is hard for a person to go through it thoroughly. So for doctors the difficulty of finding these lesions was like “identifying the needle in the haystack.”
“This illustrates of how artificial intelligence can support clinicians in making quicker, more accurate diagnoses, and has the potential to enhance surgical access and results for kids with otherwise intractable epilepsy,” the professor says.
Disease Detection in the Years Ahead
A public health expert, the vice-president of the international body's digital health and artificial intelligence section, says advanced AI systems are also helping to monitor and predict epidemics.
The expert, who presented recently at the national health summit in Wollongong, gave as an example Blue Dot, a organization set up by infectious disease specialists and which was an early detector to identify the coronavirus pandemic.
Generative AI is a additional branch of machine learning, in which the technology can generate new content based on existing information. These uses in medicine include tools such as the virtual assistant along with the automated note-takers clinicians are adopting more.
A GP representative, the president of the national GP body, reports family doctors have been adopting digital assistants, which captures the appointment and converts it to a medical summary that can be included in the health file.
Wright says the primary advantage of the scribes is that it improves the quality of the communication between the physician and individual.
Dr Danielle McMullen, the chair of the Australian Medical Association, concurs that AI note-takers are assisting doctors manage schedules and says AI can also help to prevent repeated examinations and scans for their clients, if the {promised digitisation|planned digitalization
