A senior citizen grew accustomed to receiving Aida's daily call each morning.
A routine morning call from an AI voice bot was not part of the service Rolls expected when she enrolled for St Vincent’s in-home support but when they asked to be part of the pilot program several months back, the 79-year-old agreed because she wanted to help. Although, to be honest, her hopes were low.
Even so, when the call came through, she states: “I was so overtaken by how interactive she was. It was remarkable for a machine.”
“She’d always ask ‘how are you feeling today?’ and that gives you an opportunity if you feel unwell to mention your symptoms, or I might reply ‘I’m fine, thank you’.”
“The AI would then pose follow-up questions – ‘did you manage to go outdoors today?’”
Aida would also ask what Rolls had planned for the day and “she would respond to that properly.”
“When I mentioned I’m going shopping, she’d say are you shopping for clothes or groceries? It was quite engaging.”
Bots Easing the Workload on Healthcare Staff
The trial, which has now wrapped up its initial stage, is an example in which advances in artificial intelligence are being integrated in healthcare.
Health tech firm Healthily partnered with St Vincent’s regarding the trial to use its advanced AI system to offer social interaction, as well as an option for elderly recipients to report any health issues or concerns for a caregiver to follow up.
Dean Jones, national director of St Vincent’s At Home, explains the service under evaluation does not replace any in-person visits.
“Recipients still receive a weekly personal visit, but between these meetings … the automated system enables a daily check-in, which can then flag any possible issues to either our team or a family members,” Jones says.
The managing director, the CEO of Healthily, says there haven’t been any adverse incidents noted from the St Vincent’s trial.
Healthily employs open AI “with strict safety protocols” to ensure the conversation is secure and procedures are established to address serious health issues promptly, Campbell says. As an instance, if a patient is reporting chest pains, it would be flagged to the care team and the call ended so the individual could dial triple zero.
She believes artificial intelligence has an important role given staffing shortages throughout the medical industry.
“What we can do very safely, with technology like this, is lessen the administrative load on the staff so trained clinicians can concentrate on doing the job that they specialize in,” she says.
AI Not as New as Often Believed
Prof Enrico Coiera, the co-founder of the national AI health alliance, says established types of AI have been a common feature of medicine for a considerable period, frequently in “administrative functions” such as interpreting medical images, ECGs and pathology test results.
“Software that carries out a function that involves decision making in certain aspects is artificial intelligence, irrespective of how it achieves that,” states the professor, who is also the director of the health informatics center at a leading university.
“If you go the imaging department, radiology department or diagnostic laboratory, you will find software in equipment doing just that.”
In recent years, advanced versions of artificial intelligence known as “deep learning” – a neural network method that allows algorithms to analyze very large sets of data – have been employed to interpret diagnostic scans and enhance detection, Coiera says.
Recently, a screening service became Australia’s pioneering population-based screening program to introduce AI analysis tools to assist radiologists in interpreting a select range of mammography images.
These represent specialized tools that still require a specialist doctor to evaluate the diagnosis they might suggest, and the responsibility for a clinical judgment rests with the medical practitioner, Coiera emphasizes.
The Function of AI in Early Disease Detection
A research center in Melbourne has been working alongside scientists from a UK university who pioneered AI methods to identify epilepsy brain abnormalities called specific brain malformations from MRI images.
These lesions trigger epileptic episodes that often cannot be controlled with drugs, so surgery to remove them becomes the sole option. However, the surgery can proceed if the doctors can pinpoint the abnormal tissue.
In research published this week in the journal Epilepsia, a team from the institute, headed by neurologist Emma Macdonald-Laurs, showed their “neural network tool” could detect the lesions in nearly all of cases from advanced imaging in a subtype of the malformations that have historically been missed in more than half of cases (60%).
The AI was trained on the images of 54 patients and then tested on 17 children and adult patients. Among the youngsters, 12 had surgery and 11 are now seizure free.
This technology uses neural network classifiers comparable with the mammography analysis – flagging regions of abnormality, which are still checked by experts “but it makes it a lot quicker to reach a conclusion,” Macdonald-Laurs says.
She stresses the researchers are still in the “early phases” of the project, with a additional research required to get the technology toward real-world use.
A leading neurologist, a brain specialist who was not involved in the study, says MRI scans now produce such vast quantities of high-resolution data that it is hard for a person to review it thoroughly. Thus for clinicians the challenge of finding these lesions was like “identifying the needle in the haystack.”
“It’s a great demonstration of how AI can assist doctors in making quicker, more accurate diagnoses, and has the ability to improve surgical access and results for children with otherwise intractable epilepsy,” the professor says.
Illness Identification in the Years Ahead
Dr Stefan Buttigieg, the vice-president of the international body's AI health division, explains deep neural networks are additionally used to track and forecast epidemics.
Buttigieg, who presented last month at the national health summit in the city, cited Blue Dot, a organization set up by infectious disease specialists and which was one of the first organisations to identify the coronavirus pandemic.
Generative AI is a further subset of deep learning, in which the technology can produce original material based on training data. These uses in healthcare include programs such as the virtual assistant as well as the automated note-takers clinicians are adopting more.
A GP representative, the president of the national GP body, says family doctors have been embracing AI scribes, which records the consultation and turns into a medical summary that can be added to the health file.
The president states the main benefit of the scribes is that it enhances the quality of the communication between the physician and individual.
A medical leader, the chair of the Australian Medical Association, concurs that AI note-takers are helping physicians manage schedules and adds artificial intelligence also has the potential to prevent repeated examinations and imaging for their clients, if the {promised digitisation|planned digitalization
