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Peta Rolls came to anticipate getting Aida's regular call each morning.

A daily check-in call by an automated voice assistant was not part of the care package Rolls envisioned when she enrolled for the home care but when they asked to be part of the trial several months back, the 79-year-old agreed because she wished to contribute. Although, truth be told, her hopes were low.

Nevertheless, when she got the call, she says: “I was so overtaken by how interactive she was. It was remarkable for a machine.”

“She’d always ask ‘how you are today?’ and that gives you an opportunity if you’re feeling sick to mention your symptoms, or I might reply ‘I’m fine, thank you’.”

“The AI would then pose follow-up questions – ‘have you had a chance to step outside today?’”

The virtual assistant would also ask what the user had planned for the day and “she would respond to that properly.”

“When I mentioned I plan to go shopping, it would ask are you shopping for clothes or groceries? I found it entertaining.”

Bots Easing the Administrative Burden on Medical Staff

This pilot, which has now wrapped up its initial stage, is an example in which progress in artificial intelligence are being taken up in the medical field.

Digital health company Healthily partnered with the care organization regarding the trial to use its generative AI technology to offer companionship, along with an option for home care clients to log any health issues or issues for a staff member to address.

Dean Jones, head of St Vincent’s At Home, says the service under evaluation is not a substitute for any in-person visits.

“Recipients continue to get a regular personal visit, but between these meetings … the automated system enables a daily check-in, which can then flag any potential concerns to care staff or a family members,” the director says.

Dr Tina Campbell, the managing director of Healthily, reports there have been no any adverse incidents noted from the St Vincent’s trial.

The company uses advanced AI “with very clear guardrails and prompts” to ensure the interaction is safe and procedures are established to respond to serious health issues quickly, Campbell says. As an instance, if a patient is reporting heart symptoms, it would be alerted to the medical staff and the call ended so the person could dial triple zero.

She thinks AI has an significant part amid significant workforce challenges across the healthcare sector.

“The benefit very safely, with technology like this, is lessen the administrative load on the workforce so trained clinicians can focus on performing the duties that they’re trained to do,” she says.

Artificial Intelligence Long Established as Often Believed

An expert, the founder of the Australian Alliance for Artificial Intelligence in Healthcare, explains established types of AI have been a common feature of healthcare for a long time, frequently in “back office services” such as interpreting scans, ECGs and lab reports.

“Software that performs a task that involves decision making in some way is AI, irrespective of how it achieves that,” states the professor, who is additionally the director of the Centre for Health Informatics at a leading university.

“If you go the imaging department, medical imaging center or pathology lab, you will find programs in equipment performing these tasks.”

In recent years, advanced versions of AI known as “deep learning” – an algorithmic approach that enables systems to learn from extensive datasets – have been used to read diagnostic scans and improve diagnosis, the expert says.

In November, BreastScreen NSW became Australia’s pioneering public health initiative to adopt machine reading technology to assist radiologists in reviewing a select range of mammography images.

They are specialized tools that continue to need a qualified physician to interpret the diagnosis they could indicate, and the responsibility for a medical decision sits with the medical practitioner, the professor says.

The Function of AI in Early Disease Detection

The Murdoch Children’s Research Institute in the city has been collaborating with researchers from a UK university who first developed artificial intelligence techniques to identify neurological lesions known as focal cortical dysplasias from brain scans.

These lesions cause epileptic episodes that crequently are resistant with drugs, so surgery to excise the tissue becomes the sole option. But, the surgery can only be performed if the surgeons can locate the affected area.

A study published this week in the scientific publication, a team from the research body, headed by specialist the lead researcher, showed their “neural network tool” could identify the abnormalities in nearly all of cases from advanced imaging in a subtype of the lesions that have historically been missed in the majority of patients (sixty percent).

The system was trained on the images of a group of individuals and then tested on pediatric cases and 12 adults. Of the 17 children, twelve underwent operations and 11 are now seizure free.

The tool uses AI algorithms comparable with the breast cancer screening – flagging suspicious areas, which are still checked by experts “speeding up the process to get to the answers,” the researcher explains.

She emphasises the researchers are still in the “early phases” of the work, with a additional research necessary to advance the tool toward clinical implementation.

Prof Mark Cook, a brain specialist who was independent from the study, says modern imaging now produce such vast quantities of detailed information that it is hard for a person to review it accurately. Thus for clinicians the challenge of finding these lesions was like “searching for a needle in a haystack.”

“It’s a great demonstration of how artificial intelligence can assist doctors in making quicker, more accurate diagnoses, and has the potential to enhance surgical access and results for children with treatment-resistant seizures,” Cook comments.

Illness Identification in the Future

A public health expert, the vice-president of the international body's digital health and artificial intelligence section, says deep neural networks are additionally used to monitor and predict epidemics.

The expert, who presented last month 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 Covid-19 outbreak.

Generative AI is a further subset of deep learning, in which the technology can produce original material based on training data. These uses in medicine encompass programs such as Healthily’s AI voice bot along with the automated note-takers doctors and allied health professionals are increasingly using.

A GP representative, the president of the national GP body, says GPs have been embracing digital assistants, which records the consultation and converts it to a medical summary that can be added to the health file.

Wright says the main benefit of the tools is that it enhances the standard of the communication between the doctor and patient.

Dr Danielle McMullen, the chair of the Australian Medical Association, agrees that AI note-takers are helping physicians optimise their time and says artificial intelligence also has the potential to prevent duplication of tests and scans for their clients, if the {promised digitisation|planned digitalization