🔗 Share this article

A senior citizen grew accustomed to receiving the AI's regular call each morning.

A daily check-in call by an automated voice assistant was not part of the care package the participant envisioned when she enrolled for the in-home support but when she was invited to participate in the trial several months back, the 79-year-old said yes because she wanted to help. Although, to be honest, her expectations were low.

Nevertheless, when she got the call, she states: “I was amazed by how responsive the AI was. It was impressive for a robot.”

“The system would inquire ‘how are you feeling today?’ and that provides a chance if you feel unwell to say you felt sick, or I just say ‘I’m fine, thank you’.”

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

Aida would also inquire about what Rolls was planning for the day and “she would respond to that properly.”

“If I would say I’m going shopping, it would ask are you shopping for clothes or groceries? I found it entertaining.”

AI Reducing the Workload on Healthcare Professionals

This pilot, which has recently concluded its initial stage, is an example in which progress in artificial intelligence are being taken up in healthcare.

Health tech firm Healthily partnered with St Vincent’s about the trial to utilize its generative AI technology to offer social interaction, along with an opportunity for elderly recipients to log any medical concerns or issues for a staff member to follow up.

Dean Jones, national director of St Vincent’s At Home, explains the service being trialled does not replace any in-person visits.

“Clients still receive a regular personal visit, but between these meetings … the automated system allows a daily check-in, which can then flag any possible issues to either our team or a family members,” the director notes.

The managing director, the CEO of Healthily, reports there haven’t been any adverse incidents noted from the St Vincent’s trial.

The company employs open AI “with strict safety protocols” to guarantee the interaction is secure and procedures are in place to respond to critical medical problems quickly, Campbell says. 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 believes artificial intelligence has an important role amid staffing shortages across the medical industry.

“What we can do securely, with technology like this, is lessen the administrative load on the workforce so trained clinicians can focus on doing the job that they specialize in,” she comments.

Artificial Intelligence Long Established as Often Believed

Prof Enrico Coiera, the founder of the Australian Alliance for Artificial Intelligence in Healthcare, explains older forms of artificial intelligence have been a common feature of medicine for a long time, often in “back office services” such as analyzing scans, cardiograms and lab reports.

“Any computer program that performs a task that requires judgment in some way is AI, irrespective of how it achieves that,” states Coiera, who is additionally the director of the Centre for Health Informatics at Macquarie University.

“When visiting the imaging department, medical imaging center or diagnostic laboratory, you will find programs in equipment doing just that.”

In recent years, newer forms of AI called “machine learning” – a neural network method that enables systems to analyze extensive datasets – have been used to interpret diagnostic scans and enhance detection, Coiera notes.

Recently, a screening service became the nation's first public health initiative to introduce AI analysis tools to support radiologists in interpreting a select range of mammography images.

These represent advanced systems that still require a qualified physician to evaluate the findings they might suggest, and the responsibility for a clinical judgment rests with the healthcare provider, Coiera 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 pioneered artificial intelligence techniques to identify neurological lesions known as focal cortical dysplasias from MRI images.

These lesions cause epileptic episodes that crequently cannot be controlled with drugs, meaning surgical intervention to remove them becomes the sole option. But, the procedure can proceed if the doctors can locate the affected area.

A study published this week in the scientific publication, a group from the research body, led by specialist Emma Macdonald-Laurs, demonstrated their “AI epilepsy detective” could identify the abnormalities in nearly all of cases from advanced imaging in a subtype of the malformations that have historically been overlooked in the majority of cases (sixty percent).

The AI was developed using the scans of a group of individuals and then tested on 17 children and 12 adults. Among the youngsters, twelve underwent operations and eleven became free of seizures.

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

She stresses the researchers are currently in initial stages of the project, with a additional research necessary to advance the tool heading towards real-world use.

Prof Mark Cook, a neurologist who was independent from the research, says MRI scans now generate such huge amounts of high-resolution data that it is hard for a person to go through it accurately. Thus for clinicians the difficulty 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 ability to enhance surgical access and results for kids with treatment-resistant seizures,” the professor says.

Illness Identification in the Future

Dr Stefan Buttigieg, the deputy head of the international body's digital health and artificial intelligence section, explains advanced AI systems are additionally used to track and forecast disease outbreaks.

The expert, who presented recently at the national health summit in the city, gave as an example Blue Dot, a company established by medical experts and which was an early detector to identify the Covid-19 outbreak.

Generative AI is a additional branch of machine learning, in which the system can generate new content based on training data. These uses in healthcare encompass programs such as the virtual assistant as well as the automated note-takers clinicians are increasingly using.

A GP representative, the head of the Royal Australian College of GPs, says family doctors have been adopting digital assistants, which captures the consultation and turns into a consultation note that can be included in the patient record.

Wright says the primary advantage of the tools is that it improves the standard of the interaction between the physician and individual.

A medical leader, the president of the national doctors' group, concurs that AI note-takers are helping physicians manage schedules and says AI can also help to prevent duplication of tests and scans for their clients, if the {promised digitisation|planned digitalization