Coreline Soft announces first China partnership
South Korean medical AI company Coreline Soft has entered into its first partnership in China.
It signed a memorandum of understanding with Suhai Information Technology, which reportedly runs a network of medical institutions in China. Coreline Soft will tap into this network to collect clinical data, which will help tailor its AI software offerings to local hospitals.
Besides promoting AI adoption as part of early chronic disease diagnosis, Coreline Soft and Suhai will also collaborate to research and develop new AI-based solutions, including a CDSS platform. Additionally, they will work on several government-led health research projects targeting chronic obstructive pulmonary disease and interstitial lung disease.
The Korean company has identified China, whose medical AI market is worth around 38.8 billion yuan ($5 billion), as one of the three key Asian markets it targets for expansion. It has already established its presence in both Taiwan and Japan.
Cureskin launches hair analysis AI feature
Dermatology AI company Cureskin from India has integrated a new AI feature on its mobile application that analyses hairlines and detects male pattern baldness.
According to a media release, its hair analysis model was trained using “thousands of clinical images” to identify early signs of hair recession, thinning, and density reduction. The Cureskin app also utilises advanced image processing to analyse photos of a user’s hairline.
Last year, Cureskin raised $20 million in Series B funding to enhance its AI capabilities.
Korean researchers develop lumbar stenosis AI
Researchers from Seoul National University Hospital (SNUH) have created an AI model for diagnosing lumbar spinal stenosis on X-ray images.
Based on a media release, the team utilised existing AI models to train their model with X-ray images of lumbar stenosis taken in neutral, flexed, and extended postures, which they said reduces false-positive and negative errors.
In a study, their model demonstrated 91.4% accuracy in detecting the condition using a set of X-ray images from 5,000 SNUH patients from 2005 to 2017.
Lumbar stenosis is characterised by persistent back pain due to the spinal canal narrowing and compressing the nerves connecting the lower body.
The SNUH research team is now working to integrate the AI into a commercial application.
Remidio integrates risk assessment in mobile diabetic retinopathy screening
Remidio, developer of mobile solutions for diabetic retinopathy (DR) screening in India, has recently collaborated with Iceland-based RetinaRisk for technology integration.
They integrated Remidio’s automated DR detection and baseline severity grading capabilities and RetinaRisk’s risk prediction algorithm with real-time retinal grading into mobile DR point-of-care screening. A press release noted that RetinaRisk’s algorithm has shown 85% accuracy in predicting DR and demonstrated potential to reduce screening frequency by 56%.
The partners will pilot the integrated solution in specific populations with high diabetes prevalence in India.
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