AI used for early dementia detection backed by InterSystems
, an innovative data technology provider, has announced it is partnering with to support its ‘ground-breaking’ solution that uses AI to detect dementia up to 15 years earlier than conventional methods.
Cognetivity's partnership with InterSystems grants the company access to InterSystems IRIS for Health; a data platform specifically engineered to extract value from healthcare data. Cognetivity deploys the system to power the clinical effectiveness of its Integrated Cognitive Assessment (ICA), a unique approach to the detection of dementia that tests how the brain reacts to certain types of images.
What is the Cognetivity ICA?
Non-invasive and conducted on an Apple iPad tablet, the Cognetivity ICA detects the earliest signs of disease before the onset of memory symptoms. According to Cognetivity, it has the potential to transform treatment and care for millions of people living with dementia around the globe by enabling earlier intervention to delay the onset and reduce mortality.
InterSystems IRIS for Health will facilitate the integration of the Cognetivity ICA platform with the necessary healthcare data systems, ensuring that critical information gets to the right person at the right time, a crucial element required for efficient adoption and effective decision-making.
, Chief Technology Officer, Cognetivity, said: “The unique data management and integration capabilities of InterSystems IRIS platform are essential to what we do. They give us the interoperability and agility our cutting-edge technology requires to help transform dementia care pathways right across the NHS and to meet the accelerating demand for telemedicine and remote tools.”
A Cloud-based data platform, InterSystems IRIS for Health deploys on all major public clouds and supports multi-cloud and hybrid environments. This eliminates the need to integrate multiple technologies and makes it easier to build high-performance, machine learning-enabled applications that connect data.
The Cognetivity ICA is currently the subject of a UK government-funded study in collaboration with the Sussex Partnership NHS Trust and Alzheimer’s Research UK.
Increasing use of AI in healthcare
The healthcare industry continues to evolve as the use of AI and machine learning technologies becomes more prevalent. AI can increase the ability for healthcare professionals to better understand the day-to-day patterns and needs of the people they care for. With that understanding, they can provide better feedback, guidance, and support for staying healthy.
A 2021 article reported that projects AI in healthcare will grow at an annualised 48% between 2017 and 2023. Another found that the global artificial intelligence in healthcare market revenue is expected to register a CAGR of 43.6%, and reach a market size of US$61.59 billion in 2027.
Artificial intelligence is used in research for cancer and disease management, and this is expected to drive the growth of AI in the healthcare market over the forecast period. Other areas of healthcare that AI is used in includes clinical trials, drug research, patient treatment.
Dr. Ben Lorica, the co-author of a about AI in healthcare, : “We’re at a point of inflection for AI adoption in the healthcare and life sciences industry, and understanding how organisations are applying these technologies, who is using them, and the challenges and breakthroughs they’re seeing in practice is vital to continuing our progress in the field.”
Google launches Visual Inspection AI tool for manufacturers
Google Cloud has launched Visual Inspection AI, a new tool to help manufacturers identify defects in products before they're shipped.
Poor production quality control often leads to significant operational and financial costs. The American Society for Quality estimates that for many organisations this cost of quality is as high as 15-20% of annual sales revenue, or billions of dollars annually for larger manufacturers. Google Cloud’s new Visual Inspection AI solution has been purpose-built for the industry to solve this problem at production scale.
How does it work?
The Google Cloud Visual Inspection AI solution automates visual inspection tasks using a set of AI and computer vision technologies that enable manufacturers to transform quality control processes by automatically detecting product defects.
Google built Visual Inspection AI to meet the needs of quality, test, manufacturing, and process engineers who are experts in their domain, but not in AI.
- Run autonomously on-premises: Manufacturers can run inspection models at the network edge or on-premises. The inspection can run either in Google Cloud or fully autonomous on your factory shop floor.
- Short time-to-value: Customers can deploy in weeks, not the months typical of traditional machine learning (ML) solutions. Built for process and quality engineers, no computer vision or ML experience required. An interactive user interface guides users through all the steps.
- Superior computer vision and AI technology: In production trials, Visual Inspection AI customers improved accuracy by up to 10x compared with general-purpose ML approaches, according to benchmarks from several Google Cloud customers.
- Get started quickly, with little effort: Visual Inspection AI can build accurate models with up to 300x fewer human-labeled images than general-purpose ML platforms, based on pilots run by several Google Cloud customers.
- Highly scalable deployment: Manufacturers can flexibly deploy and manage the lifecycle of ML models, scaling the solution across production lines and factories.
Industry use cases
The demo video shows how Visual Inspection AI addresses use cases to solve specific quality control problems in industries such as automotive manufacturing, semiconductor manufacturing, electronics manufacturing and general-purpose manufacturing.
Kyocera Communications Systems, a manufacturer of mobile phones for wireless service providers, has been able to scale its AI and ML expertise through the use of the solution. “With the shortage of AI engineers, Visual Inspection AI is an innovative service that can be used by non-AI engineers,” said Masaharu Akieda, Division Manager, Digital Solution Division, KYOCERA Communication Systems. “We have found that we are able to create highly accurate models with as few as 10-20 defective images with Visual Inspection AI. We will continue to strengthen our partnership with Google to develop solutions that will lead our customers' digital transformation projects to success.”
Visual Inspection AI has fully integrated with Google Cloud's portfolio of analytics and ML/AI solutions, giving manufacturers the ability to combine its insights with other data sources. The tool integrates with existing products from Google Cloud partners, including SOTEC, Siemens, GFT, QuantiPhi, Kyocer and Accenture.