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A senior citizen came to anticipate receiving the AI's regular call each morning.

A daily check-in call by an automated voice assistant wasn't initially included in the service 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 elderly lady agreed because she wished to contribute. Even though, to be honest, her expectations weren't high.

Nevertheless, when the call came through, she says: “I was so overtaken by how interactive she was. It was impressive for a robot.”

“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 just say ‘I’m fine, thank you’.”

“She would go on to ask follow-up questions – ‘did you manage to go outdoors today?’”

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

“When I mentioned I plan to go shopping, she’d say are you shopping for clothes or groceries? I found it entertaining.”

AI Reducing the Workload on Healthcare Staff

The trial, 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.

Health tech firm the provider approached St Vincent’s regarding the trial to utilize its generative AI technology to offer social interaction, as well as an option for home care clients to report any health issues or issues for a staff member to address.

Dean Jones, head of St Vincent’s At Home, explains the AI check-in under evaluation does not replace any in-person visits.

“Recipients continue to get a regular face to face meeting, but between these meetings … the [AI] system allows a routine call, which can then flag any possible issues to either our team or a client’s family,” 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.

Healthily employs advanced AI “with very clear guardrails and prompts” to ensure the interaction is secure and mechanisms are in place to respond to critical medical problems quickly, the director says. As an instance, if a client is reporting heart symptoms, it would be flagged to the care team and the call ended so the individual could dial triple zero.

She thinks AI has an important role amid significant workforce challenges across the medical industry.

“The benefit very safely, with technology like this, is reduce the administrative load on the workforce so trained clinicians can concentrate on doing the job that they specialize in,” she says.

Artificial Intelligence Long Established as Often Believed

An expert, the founder of the national AI health alliance, says older forms of AI have been a common feature of medicine for a long time, frequently in “administrative functions” such as analyzing scans, cardiograms and lab reports.

“Software that carries out a function that involves decision making in some way is AI, irrespective of how it achieves that,” says the professor, who is additionally the director of the health informatics center at Macquarie University.

“If you go the radiology unit, radiology department or diagnostic laboratory, you will find programs in equipment doing just that.”

In recent years, advanced versions of artificial intelligence called “machine learning” – an algorithmic approach that enables algorithms to learn from very large sets of data – have been employed to interpret diagnostic scans and enhance detection, the expert notes.

In November, BreastScreen NSW became the nation's first public health initiative to introduce AI analysis tools to support specialists in interpreting a select range of breast scans.

They are specialized tools that still require a specialist doctor to interpret the diagnosis they could indicate, and the accountability for a medical decision sits with the healthcare provider, the professor says.

AI’s Role in Early Disease Detection

The Murdoch Children’s Research Institute in Melbourne has been working alongside researchers from UCL London who pioneered artificial intelligence techniques to identify neurological lesions known as specific brain malformations from MRI images.

These lesions trigger epileptic episodes that crequently cannot be controlled with medication, so surgical intervention to excise the tissue becomes the only treatment available. But, the surgery can only be performed if the surgeons can locate the abnormal tissue.

In research published this week in the scientific publication, a group from the research body, led by neurologist the lead researcher, showed their “neural network tool” could identify the lesions in up to 94% of cases from advanced imaging in a subtype of the lesions that have historically been overlooked in the majority of patients (sixty percent).

The AI was developed using the scans of 54 patients and then evaluated with 17 children and 12 adults. Of the 17 children, 12 had surgery and 11 are now seizure free.

The tool uses neural network classifiers similar to the mammography analysis – highlighting regions of abnormality, which are subsequently reviewed by experts “but it makes it a lot quicker to reach a conclusion,” Macdonald-Laurs explains.

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

Prof Mark Cook, a brain specialist who was independent from the research, says MRI scans now generate such huge amounts of high-resolution data that it is challenging for a person to go through it accurately. Thus for clinicians the challenge of locating these lesions was like “identifying the needle in the haystack.”

“It’s a great demonstration of how AI can support clinicians in making earlier, precise identifications, and has the potential to enhance operation opportunities and results for children with treatment-resistant seizures,” the professor comments.

Illness Identification in the Future

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 spoke recently at the national health summit in the city, cited Blue Dot, a organization set up by infectious disease specialists and which was an early detector to detect the Covid-19 outbreak.

Content-creating AI is a additional branch of deep learning, in which the system can generate new content based on training data. These uses in healthcare encompass programs such as Healthily’s AI voice bot as well as the AI scribes doctors and allied health professionals are increasingly using.

Dr Michael Wright, the head of the national GP body, reports GPs have been embracing digital assistants, which records the consultation and turns into a consultation note that can be included in the health file.

Wright says the primary advantage of the tools is that it enhances the standard of the interaction between the doctor and patient.

Dr Danielle McMullen, the chair of the Australian Medical Association, agrees that AI note-takers are assisting doctors optimise their time and adds AI also has the potential to help doctors avoid duplication of tests and scans for their patients, if the {promised digitisation|planned digitalization