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Peta Rolls came to anticipate getting the AI's daily call at 10am.

A routine morning call by an automated voice assistant was not part of the service the participant envisioned when she signed up for the in-home support but when they asked to be part of the pilot program several months back, the 79-year-old said yes because she wished to contribute. Even though, to be honest, her hopes weren't high.

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

“The system would inquire ‘how you are today?’ and that gives you an opportunity if you feel unwell to say you felt sick, or I just say ‘I'm well, thanks’.”

“She would go on to ask questions – ‘have you had a chance to step outside today?’”

The virtual assistant would also inquire about what the user was planning for the day and “she would respond to that properly.”

“When I mentioned I’m going shopping, she’d say nice shopping or food shopping? I found it entertaining.”

Bots Easing the Administrative Burden on Healthcare Staff

The trial, which has now wrapped up its first phase, is one of the ways in which progress in AI technology are being integrated in healthcare.

Digital health company the provider partnered with the care organization about the trial to use its generative AI technology to provide companionship, along with an option for elderly recipients to report any medical concerns or concerns for a staff member to address.

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

“Clients continue to get a weekly personal visit, but between these meetings … the [AI] system enables a routine call, which can then escalate any potential concerns to either our team or a family members,” the director notes.

The managing director, the managing director of the company, says there haven’t been any negative events noted from the pilot program.

The company employs open AI “with very clear guardrails and prompts” to ensure the interaction is secure and mechanisms are in place to address critical medical problems promptly, the director states. For example, if a client is experiencing chest pains, it would be flagged to the care team and the conversation terminated so the individual could call emergency services.

She thinks artificial intelligence has an significant part given significant workforce challenges throughout the healthcare sector.

“The benefit securely, using such systems, is lessen the administrative load on the workforce so trained clinicians can concentrate 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, explains established types of artificial intelligence have been a standard part of healthcare for a long time, often in “administrative functions” such as interpreting medical images, cardiograms and lab reports.

“Any computer program that performs a task that involves decision making in certain aspects is artificial intelligence, irrespective of how it achieves that,” says Coiera, who is additionally the head of the Centre for Health Informatics at a leading university.

“If you go the imaging department, medical imaging center or diagnostic laboratory, you will find software in equipment doing just that.”

In recent years, advanced versions of AI called “deep learning” – a neural network method that allows systems to analyze very large sets of data – have been used to interpret medical imaging and enhance detection, the expert says.

In November, BreastScreen NSW became the nation's pioneering public health initiative to adopt machine reading technology to assist specialists in interpreting a specific set of mammography images.

They are advanced systems that still require a qualified physician to interpret the diagnosis they could indicate, and the responsibility for a medical decision rests with the healthcare provider, Coiera says.

AI’s Role in Early Disease Detection

A research center in the city has been collaborating with scientists from a UK university who first developed artificial intelligence techniques to identify neurological lesions called specific brain malformations from brain scans.

These lesions trigger epileptic episodes that often are resistant with medication, meaning surgery to remove them becomes the only treatment available. But, the procedure 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 institute, headed by specialist Emma Macdonald-Laurs, showed their “neural network tool” could detect the lesions in nearly all of instances from advanced imaging in a subtype of the lesions that have historically been missed in more than half of patients (60%).

The AI was trained on the scans of 54 patients and then evaluated with pediatric cases and adult patients. Of the 17 children, twelve underwent operations and eleven became free of seizures.

This technology employs AI algorithms similar to the mammography analysis – flagging regions of abnormality, which are subsequently reviewed by specialists “speeding up the process to reach a conclusion,” Macdonald-Laurs says.

She emphasises the researchers are still in the “early phases” of the work, with a further study required to get the technology heading towards real-world use.

Prof Mark Cook, a brain specialist who was not involved in the study, notes modern imaging now generate such huge amounts of high-resolution data that it is challenging for a human to go through it thoroughly. So for doctors the challenge of locating these lesions was like “searching for a needle in a haystack.”

“It’s a great demonstration of how AI can assist doctors in making earlier, precise identifications, and has the potential to improve operation opportunities and outcomes for children with treatment-resistant seizures,” Cook says.

Illness Identification in the Future

Dr Stefan Buttigieg, the deputy head of the European Public Health Association’s digital health and artificial intelligence section, explains deep neural networks are also helping to track and forecast epidemics.

Buttigieg, who spoke recently at the national health summit in the city, cited a tech firm, a organization set up by infectious disease specialists and which was one of the first organisations to detect the Covid-19 outbreak.

Content-creating AI is a additional branch of deep learning, in which the system can generate new content using existing information. These uses in healthcare include programs such as the virtual assistant as well as the automated note-takers doctors and allied health professionals are increasingly using.

Dr Michael Wright, the head of the Royal Australian College of GPs, says family doctors have been embracing AI scribes, which records the appointment and turns into a medical summary that can be added to the patient record.

The president says the main benefit of the scribes is that it improves the standard of the interaction between the doctor and patient.

Dr Danielle McMullen, the chair of the Australian Medical Association, agrees that scribes are helping physicians optimise their time and says artificial intelligence also has the potential to prevent repeated examinations and scans for their patients, if the {promised digitisation|planned digitalization