AI detects brain lesions with 94% accuracy in Australian healthcare

Australia’s healthcare system is embracing artificial intelligence through innovations ranging from daily check-in chatbots for home care patients to AI “detectives” that can identify brain lesions in medical scans with up to 94% accuracy. These developments represent a significant expansion of AI applications beyond traditional back-office medical tasks, with experts emphasizing that healthcare AI adoption is still in its early phases despite already showing measurable benefits for both patients and healthcare workers.

What you should know: AI chatbots are providing daily social interaction and health monitoring for home care patients, with promising results from early trials.

• St Vincent’s At Home, a healthcare service provider, partnered with digital health company Healthily to trial an AI voice bot named Aida that calls patients daily at 10am to check on their wellbeing and escalate concerns to care teams when necessary.
• Peta Rolls, a 79-year-old trial participant, described the experience as “impressive for a robot,” noting how Aida would ask follow-up questions and respond appropriately to her daily activities.
• The service doesn’t replace face-to-face meetings but provides daily check-ins between weekly in-person visits, with built-in safety mechanisms to handle serious health issues.

AI’s diagnostic breakthrough: Researchers at Melbourne’s Murdoch Children’s Research Institute developed an “AI epilepsy detective” that dramatically improves detection of brain lesions causing seizures.

• The AI system can detect focal cortical dysplasias—brain abnormalities that cause seizures—in up to 94% of cases from MRI and PET scans, compared to traditional methods that miss these lesions in more than 60% of cases.
• Of 17 children in the study, 12 had surgery based on AI-detected lesions and 11 are now seizure-free.
• The technology uses neural network classifiers to highlight abnormal regions, which experts then verify, significantly speeding up diagnosis.

The bigger picture: AI integration in healthcare extends far beyond recent chatbot developments, with older AI systems already standard in medical imaging, pathology labs, and diagnostic equipment.

• Prof Enrico Coiera from the Australian Alliance for Artificial Intelligence in Healthcare notes that “any computer program that carries out a task that involves decision making in some way is AI.”
• BreastScreen NSW became Australia’s first population-based screening program to introduce machine reading technology for mammography interpretation in November.
• Deep learning AI methods—neural networks that learn from large datasets—have been used for medical imaging and diagnosis improvement over the past decade.

Administrative efficiency gains: Healthcare professionals are increasingly adopting AI scribes and voice assistants to reduce administrative burdens and improve patient interactions.

• Dr Michael Wright, president of the Royal Australian College of GPs, says AI scribes record consultations and convert them into patient notes, improving doctor-patient interaction quality.
• Dr Tina Campbell from Healthily emphasizes that AI can “reduce the admin burden on the workforce so qualified health professionals can focus on doing the job that they’re trained to do.”
• The technology addresses significant workforce challenges across Australia’s healthcare sector.

What they’re saying: Medical professionals highlight AI’s potential while emphasizing human oversight remains essential.

• “It’s a great demonstration of how AI can support clinicians in making earlier, more accurate diagnoses, and has the potential to improve surgical access and outcomes for kids with otherwise intractable epilepsy,” said Prof Mark Cook, a neurologist not involved in the epilepsy study.
• Dr Stefan Buttigieg from the European Public Health Association notes AI’s potential for personalized healthcare: “For many years healthcare was delivered using tools and solutions that are one-size fits-all… but now we are looking towards the future where there are more refined solutions.”

Looking ahead: Experts predict AI will enable increasingly personalized healthcare delivery and continue supporting disease detection and outbreak monitoring.

• Deep neural networks are already helping monitor and predict disease outbreaks, with companies like Blue Dot among the first to detect the Covid-19 outbreak.
• Future applications include helping doctors avoid duplicate tests and scans through promised digitization of health records.
• Researchers emphasize they’re still in “early phases” of AI healthcare implementation, with further studies needed before widespread clinical deployment.