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Peta Rolls grew accustomed to receiving Aida's daily call each morning.

A routine morning call by an automated voice assistant was not part of the service Rolls envisioned when she enrolled for St Vincent’s in-home support however when they asked to participate in the pilot program several months back, the elderly lady agreed because she wished to contribute. Although, to be honest, her expectations weren't high.

Even so, when she got the call, she states: “I was so overtaken by how responsive she was. It was impressive for a robot.”

“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 just say ‘I'm well, thanks’.”

“The AI would then pose follow-up questions – ‘did you manage to go outdoors today?’”

Aida would also ask what the user was planning 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.”

AI Reducing the Workload on Medical Professionals

The trial, which has now wrapped up its initial stage, is an example in which advances in artificial intelligence are being taken up in the medical field.

Digital health company Healthily approached the care organization about the program to use its advanced AI system to offer companionship, along with an option for elderly recipients to report any medical concerns or issues for a caregiver to follow up.

A senior director, national director of St Vincent’s At Home, says the AI check-in being trialled does not replace any face to face interactions.

“Clients continue to get a regular face to face meeting, but between these meetings … the automated system enables a daily check-in, which can then flag any possible issues to care staff or a client’s family,” Jones says.

Dr Tina Campbell, the CEO of Healthily, says there haven’t been any negative events reported from the pilot program.

Healthily uses advanced AI “with very clear guardrails and prompts” to guarantee the conversation is safe and mechanisms are in place to respond to critical medical problems promptly, Campbell states. As an instance, if a client is experiencing heart symptoms, it would be flagged to the medical staff and the call ended so the person could dial triple zero.

Campbell believes AI has an important role given staffing shortages throughout the medical industry.

“The benefit securely, with technology like this, is reduce the admin burden on the staff so qualified health professionals can concentrate on doing the job that they specialize in,” she says.

AI Not as New as Often Believed

An expert, the founder of the Australian Alliance for Artificial Intelligence in Healthcare, says established types of artificial intelligence have been a standard part of medicine for a considerable period, often in “administrative functions” such as analyzing medical images, ECGs and pathology test results.

“Software that performs a task that involves decision making in some way is artificial intelligence, irrespective of how it accomplishes it,” says Coiera, who is additionally the head of the Centre for Health Informatics at a leading university.

“When visiting the imaging department, radiology department or diagnostic laboratory, you’ll see software in equipment doing just that.”

Over the past decade, advanced versions of AI called “deep learning” – an algorithmic approach that enables systems to analyze very large sets of data – have been employed to read medical imaging and improve diagnosis, the expert says.

Recently, a screening service became the nation's pioneering population-based screening program to adopt AI analysis tools to assist specialists in interpreting a select range of breast scans.

They are specialized tools that continue to need a specialist doctor to evaluate the diagnosis they could indicate, and the accountability for a clinical judgment rests with the medical practitioner, Coiera says.

AI’s Role in Early Disease Detection

A research center in Melbourne has been collaborating with researchers from UCL London who first developed AI methods to identify neurological lesions known as focal cortical dysplasias from brain scans.

These abnormalities cause epileptic episodes that often are resistant with drugs, meaning surgical intervention to excise the tissue becomes the sole option. But, the surgery can only be performed if the surgeons can locate the affected area.

In research published this week in the scientific publication, a group from the institute, headed by specialist Emma Macdonald-Laurs, showed their “neural network tool” could identify the lesions in up to 94% of instances from MRI and PET scans in a specific form of the malformations that have historically been missed in more than half of cases (60%).

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

This technology employs 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,” the researcher explains.

She stresses the researchers are currently in initial stages of the project, with a further study required to get the technology heading towards clinical implementation.

Prof Mark Cook, a neurologist who was independent from the research, says MRI scans now generate such huge amounts of detailed information that it is hard for a person to review it thoroughly. So for doctors the challenge of finding these lesions was like “identifying the needle in the haystack.”

“It’s a great demonstration of how artificial intelligence can support clinicians in making earlier, precise identifications, and has the potential to enhance operation opportunities and results for kids with otherwise intractable epilepsy,” Cook comments.

Illness Identification in the Years Ahead

Dr Stefan Buttigieg, the vice-president of the European Public Health Association’s digital health and artificial intelligence section, explains deep neural networks are additionally used to monitor and predict disease outbreaks.

The expert, who presented recently at the national health summit in Wollongong, cited a tech firm, a organization established by infectious disease specialists and which was an early detector to detect the coronavirus pandemic.

Generative AI is a further subset of machine learning, in which the system can produce original material using training data. These uses in medicine encompass programs such as Healthily’s AI voice bot as well as the AI scribes doctors and allied health professionals are increasingly using.

A GP representative, the head of the Royal Australian College of GPs, reports GPs have been adopting digital assistants, which captures the appointment and turns into a consultation note that can be included in the health file.

Wright states the main benefit of the tools is that it enhances the standard of the communication between the physician and individual.

A medical leader, the president of the Australian Medical Association, concurs that scribes are helping doctors optimise their time and says AI can also help to help doctors avoid repeated examinations and imaging for their patients, if the {promised digitisation|planned digitalization