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

A daily check-in call from an AI voice bot was not part of the service the participant envisioned when she enrolled for St Vincent’s home care however when she was invited to participate in the pilot program several months back, the elderly lady agreed because she wanted to help. Although, truth be told, her hopes weren't high.

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

“The system would inquire ‘how you are today?’ and that gives you an opportunity if you’re feeling sick 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 ask 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 Workload on Medical Professionals

This pilot, which has now wrapped up its first phase, is an example in which progress in artificial intelligence are being taken up in healthcare.

Health tech firm Healthily approached St Vincent’s about the trial to utilize its generative AI technology to offer companionship, along with an option for elderly recipients to log any medical concerns 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 face to face interactions.

“Recipients still receive a regular face to face meeting, but in between visits … the automated system enables a routine call, which can then flag any possible issues to care staff or a client’s family,” Jones says.

Dr Tina Campbell, the managing director of the company, says there have been no any adverse incidents reported from the pilot program.

Healthily uses open AI “with strict safety protocols” to guarantee the conversation is secure and procedures are in place to respond to serious health issues promptly, the director says. For example, if a client is reporting chest pains, it would be alerted to the care team and the conversation ended so the person could call emergency services.

Campbell believes AI has an significant part amid staffing shortages across the medical industry.

“The benefit securely, using such systems, is reduce the administrative load on the staff so trained clinicians can concentrate on doing the job that they specialize in,” she comments.

Artificial Intelligence Long Established as You Might Think

An expert, the founder of the Australian Alliance for Artificial Intelligence in Healthcare, explains established types of artificial intelligence have been a common feature of medicine for a considerable period, frequently in “administrative functions” such as analyzing medical images, cardiograms and pathology test results.

“Any computer program that carries out a function that requires judgment in certain aspects is artificial intelligence, irrespective of how it accomplishes it,” says Coiera, who is also the director of the health informatics center at Macquarie University.

“If you go the radiology unit, radiology department or pathology lab, you will find software in machines doing just that.”

In recent years, newer forms of artificial intelligence known as “deep learning” – a neural network method that enables algorithms to learn from very large sets of data – have been used to interpret medical imaging and enhance detection, the expert notes.

In November, a screening service became the nation's first population-based screening program to adopt machine reading technology to assist radiologists in reviewing a specific set of breast scans.

These represent advanced systems that continue to need a specialist doctor to interpret the findings they might suggest, and the accountability for a medical decision sits with the healthcare provider, the professor emphasizes.

AI’s Role in Identifying Illness Early

The Murdoch Children’s Research Institute in Melbourne has been working alongside scientists from UCL London who first developed AI methods to identify epilepsy brain abnormalities called specific brain malformations 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. However, the procedure can proceed if the surgeons can pinpoint the abnormal tissue.

A study recently released in the scientific publication, a team from the institute, led by specialist Emma Macdonald-Laurs, showed their “neural network tool” could identify the lesions in nearly all of instances from MRI and PET scans in a subtype of the malformations that have traditionally been overlooked in the majority of patients (sixty percent).

The AI was trained on the images of 54 patients and then tested on pediatric cases and 12 adults. Of the 17 children, 12 had surgery and 11 are now seizure free.

This technology employs AI algorithms comparable with the mammography analysis – highlighting regions of abnormality, which are still checked by specialists “but it makes it a lot quicker to get to the answers,” the researcher says.

She emphasises the team 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 produce such huge amounts of high-resolution data that it is challenging for a human to go through it accurately. Thus for clinicians the difficulty of locating these lesions was like “searching for a needle in a haystack.”

“It’s a great demonstration of how artificial intelligence can support clinicians in making earlier, precise identifications, and has the potential to enhance surgical access and outcomes for kids with treatment-resistant seizures,” Cook comments.

Disease Detection in the Future

Dr Stefan Buttigieg, the vice-president of the European Public Health Association’s AI health division, explains deep neural networks are additionally used to track and forecast disease outbreaks.

The expert, who spoke last month at the Public Health of Australia’s conference in the city, gave as an example Blue Dot, a company set up by infectious disease specialists and which was one of the first organisations to identify the coronavirus pandemic.

Content-creating AI is a additional branch of machine learning, in which the technology can generate new content based on existing information. Such applications in medicine include programs such as the virtual assistant as well as the AI scribes clinicians are adopting more.

A GP representative, the head of the national GP body, reports GPs have been adopting digital assistants, which records the appointment and converts it to a medical summary that can be added to the patient record.

The president says the main benefit of the tools is that it enhances the quality of the communication between the doctor and patient.

A medical leader, the chair of the Australian Medical Association, concurs that scribes are assisting doctors manage schedules and says artificial intelligence also has the potential to prevent repeated examinations and imaging for their patients, if the {promised digitisation|planned digitalization