Researchers from the University of New South Wales and Boston University have developed an AI tool called CRANK-MS that can predict Parkinson’s disease before symptoms appear by analyzing blood samples for unique combinations of metabolites. Another study from the University of Western Australia demonstrates how machine learning and data analysis can help identify patients at high risk of cardiovascular complications after non-cardiac surgeries. Medtech company HeraMED has signed a contract with Joondalup Obstetrics and Gynaecology Group to provide remote pregnancy monitoring solutions. New Zealand-based Formus Labs has received FDA clearance for its AI-powered software for hip surgery planning.
ML tool predicts Parkinson’s onset
A research team from the University of New South Wales, together with their collaborators from Boston University, has come up with an AI tool that could be potentially used to predict Parkinson’s disease years before the onset of initial symptoms.
The machine learning tool called CRANK-MS, (Classification and Ranking Analysis using Neural network generates Knowledge from Mass Spectrometry) was used to analyse potential biomarkers of Parkinson’s in a patient’s blood.
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In a study, which findings have been published in the journal ACS Central Science, blood samples from 39 patients who developed Parkinson’s up to 15 years later were analysed and compared to blood samples of 39 matched patients who did not develop the disease.
After running CRANK-MS over the participants’ data on their blood metabolites, the research team found unique combinations of metabolites that could serve as early warning signs for Parkinson’s.
AI shows promise to prevent deaths after non-cardiac surgery
Another study has shown how data and AI can help prevent cardiovascular complications after non-cardiac surgeries.
A study led by a researcher from the University of Western Australia evaluated data from over 24,000 participants to determine whether machine learning and data could predict cardiovascular complications from non-heart surgery, including heart attack and injury to the heart muscle, before they occur.
It found that integrating machine learning techniques with routinely collected data before, during, and after surgery could help better identify patients at the highest risk of having such deadly complications.
“Further work is planned to fine-tune these methods and to embed them into routine care,” said Graham Hillis, a medicine professor at UWA and cardiology head at Royal Perth Hospital.
HeraMED to deliver remote pregnancy monitoring solutions to Perth-based JOGG
ASX-listed medtech company HeraMED has signed its second private obstetrician practice that is adopting its remote pregnancy monitoring solutions.
In a corporate disclosure, the company said it signed a contract with Perth-based Joondalup Obstetrics and Gynaecology Group (JOGG), a provider of private and public obstetric services across Joondalup Private Hospital, Joondalup Health Campus, and Fiona Stanley Hospital.
The contract, which represents the first time JOGG is offering remote pregnancy monitoring since it launched in 2021, is for acquiring 120 licenses of HeraCARE digital maternity monitoring and management platform and HeraBEAT at-home fetal heart rate monitors.
Last year in November, HeraMED signed its first private obstetrician practice that deployed HeraCARE.
Formus Labs gets US FDA 510(k) for hip surgery planning software
New Zealand-based Formus Labs has obtained the United States Food and Drug Administration’s 510(k) clearance for its automated radiological image processing software for pre-op planning of hip replacement.
Formus Hip uses AI and computational biomechanics to calculate a patient’s implant fit and generate “digestible, actionable and fully-interactive” 3D surgical plans.
Following its FDA clearance, the company will now proceed with its plan to fully enter the US market.
Source: MobihealthNews
