Jul 21, 2020

How AI systems detected the first COVID-19 case

ai systems
covid-19
Artificial intelligence
patient zero
Emily Cook
2 min
coronavirus covid-19 first case patient zero in wuhan, china detected by ai artificial intelligence systems
AI from the Global Disease Monitoring Systems were the first to see patient zero of COVID-19 in Wuhan...

On December 30th, two global disease monitoring health systems were triggered as the first cases of the COVID-19 pandemic. ProMED retrieved information on unexplained pneumonia cases in Wuhan, China. This information was retrieved via an artificial intelligences system that scans social media channels such as China’s microblogging site, Weibo. Simultaneously, HealthMap detected a health report regarding an unidentified respiratory illness outbreak in Wuhan with 27 reported cases. 

ProMED 

The Program for Monitoring Emerging Diseases otherwise known as ProMED is a program of the International Society for Infectious Diseases (ISID). It was founded in 1994 and began as an online scientist-to-scientist network to identify abnormal health events which then evolved to an outbreak report list soon after the 1995 Ebola outbreak. 

ProMED has been the first to report on many global disease outbreaks including SARS, MERS, Ebola and Zika. It runs for 24 hours a day, 7 days a week and with teams in over 32 countries across the globe, ProMED will continue to be an important system to detect global outbreaks of infectious diseases.

HealthMap 

The second AI system to be triggered on December30th was HealthMap, founded in 2006 by software developers and researchers at Boston Children’s Hospital . The 9 language system detects global health threats by scanning, filtering and organising data sources such as official reports, eyewitness accounts and online news feeds for real-time information. The system is a free-to-use website and app that can detect disease outbreaks in your near-by area and supports situational awareness. 

AI battling COVID-19

Even after detecting the outbreak in December 2019, AI technology has assisted medical health teams worldwide in the spread of COVID-19. It has many diverse tasks such as searching for vaccines, processing lung scans and predicting the evolution of the pandemic. 

AI systems are very complex machines and it currently plays a huge role in finding a cure to this disease. An Oxford-based system called Exscientia and a Cambridge company, Healx are processing large amounts of data to find a successful cure.

It does this in 3 parts; scan through all current reports on the disease, study the DNA and structure of the virus and then consider the suitability of various drugs. The outcome would involve one of two options, create an entirely new drug that would take a couple years to be approved or repurpose existing drug. 

AI systems are impressive displays of machine intelligence that simulate human tasks at insane speeds. In current climate, computer science and AI have assisted healthcare professionals in a plethora of ways, helping to speed up and automate human problem solving. AI not only detected COVID-19 but it is working endlessly to battle it. 

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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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