Apr 6, 2021

Rackspace survey finds rise in AI use for predictive models

AI
ML
cloudtechnology
predictivemodelling
Leila Hawkins
2 min
Rackspace survey finds rise in AI use for predictive models
The Rackspace study reveals that healthcare IT leaders are using AI and ML for predictive modelling as well as to predict business performance and risk...

Research by global multicloud computing company Rackspace Technologies has found that artificial intelligence (AI) and machine learning (ML) have emerged as key technologies during the pandemic, particularly to help healthcare providers improve predictive models. 

Rackspace surveyed 1,870 IT leaders in a range of sectors including manufacturing, finance, retail, government and healthcare, across the Americas, Europe, Asia and the Middle East. Respondents were asked about AI and machine learning usage within their organisation, along with benefits, impacts and what future plans they have. 

Among the findings, a third (32%) of healthcare IT professionals said they plan to use AI/ML for data analytics, to predict risk (27%), and to to predict business performance (27%). 

Jeff DeVerter, Rackspace Technologies CTO, says that COVID-19 has demonstrated the benefits of these technologies to improve predictions in the healthcare sector. "Healthcare is one of the industries which is seeing real benefits today" he says. "AI/ML is being used extensively to create COVID-19 infection models, as well as in care facilities in helping to optimise logistics through predictive models on which they need specific medical equipment or supplies." 

Around a third of respondents also said they will use AI/ML for resource optimisation (28%) and for embedded systems (27%). "There is so much repetitive work within healthcare organisations which makes that industry particularly ripe for AI/ML to not only create needed efficiencies but also to increase the quality of care" DeVerter explains. "Reading x-rays, diagnosis, scheduling, and predicting illness recurrence are just a few of the areas where we will see incredible advances though AI/ML."

The survey also looked at challenges to adoption, finding that barriers directly related to strategic issues like data security, identifying appropriate business cases, and a lack of confidence in data quality were the most typical problems across all levels of digital maturity. 

"One of the largest barriers to any organisation in any industry with AI/ML is the quality of the data which is analysed by the models" DeVerter adds. "If the integrity of the data and the people workflows aren’t trusted and of a high quality – the models will give false data. Healthcare organisations need to begin the process of data modernisation now to be able to utilize AI/ML tomorrow." 

Read the full report by visiting Rackspace: Tackling AI and Machine Learning’s Biggest Barrier  

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Jun 24, 2021

Jvion launches AI-powered map to tackle mental health crisis

AI
mentalhealth
dataanalytics
PredictiveAnalytics
2 min
Jvion's new interactive map uses AI to predict areas most vulnerable to poor mental health

Clinical AI company Jvion has launched an interactive map  of the US that highlights areas that are most vulnerable to poor mental health. 

The Behavioral Health Vulnerability Map uses Jvion's AI CORE™ software to analyse public data on social determinants of health (SDOH)  and determine the vulnerability of every US Census block group. 

Vulnerability refers to the likelihood that residents will experience issues like self-harm, suicide attempts or overdoses. The map also identifies the most influential social determinants in each region, to show the social and environmental conditions that contribute to mental illness. 

As an example, the map shows that Harrison County in Mississippi has a 50% higher suicide rate than the rest of the state. It also shows a high percentage of individuals in the armed forces at a time when active duty suicides are at a six-year high, along with a high prevalence of coronary artery disease, arthritis, and COPD, all chronic illnesses that are linked to a higher suicide risk.  

The map also shows Harrison County has a high percentage of Vietnamese Americans, who studies suggest have high rates of depression and may be less likely to seek help from mental health professionals. 

The map was built using the same data and analytics that Jvion used to create the COVID Community Vulnerability Map, which was launched towards the start of the pandemic. 

With this new map, Jvion is aiming to tackle the growing mental health crisis in the US. “At a time when so many Americans are struggling with their mental health, we’re proud to offer a tool that can help direct treatment resources to the communities that need it most,” said Dr John Showalter, MD, Jvion’s chief product officer, who led the development of the map. 

“For too long, the healthcare industry has struggled to address social determinants of health, particularly in the context of behavioural health. Our hope is that by surfacing the social and environmental vulnerabilities of America’s communities, we can better coordinate our response to the underlying conditions that impact the health and wellbeing of people everywhere.” 

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