MedShr Insights and Early Warning System, led by UK cardiologist Dr Asif Qasim, has been awarded a $660,000 prize in the inaugural Trinity Challenge. Drawing from real clinical case discussions posted by its 1.6 million members, MedShr Insights and Early Warning System will apply natural language processing, machine learning, and AI to identify trending medical terms and symptoms and thereby predict potential outbreaks.
MedShr enables doctors to use their smartphone to safely share and discuss anonymized clinical cases with peers around the globe. Their discussions range from straightforward clinical cases and images to diagnostic dilemmas, alongside X-rays, ECGs, blood results, medical imaging, and more. With many conferences and courses transitioning to digital formats, physicians now also share interesting academic papers, webinars, podcasts, and medical education.
With a global community of 1.6 million members in 195 countries, MedShr is uniquely positioned to identify patterns and trends from real world medical practice. This provides an opportunity to detect novel and emerging healthcare challenges.
MedShr’s response to the COVID-19 pandemic illustrates the potential impact. As COVID-19 emerged in early 2020, the MedShr team saw a corresponding increase in the number of X-rays posted on the platform, and increasing mentions of fever, dry cough and loss of sense of smell—symptoms we now know are associated with coronavirus.
Responding to these emerging trends, MedShr’s engineering, data, and clinical teams came together to rapidly develop new features, secure global knowledge-sharing groups, and free medical education programs to support its clinical members through one of the most challenging periods in recent history. This included MedShr Polls and MedShr Learning, an interactive online medical education platform.
Data from these new features and programs, combined with clinical case discussions and other contextual information, allowed the MedShr team to quickly address the knowledge gaps, amplifying targeted medical education to the healthcare professionals who needed it most.
MedShr Insights and Early Warning System aims to identify future outbreaks of this and other diseases at the earliest possible stage using medical natural language processing, machine learning, AI, and social listening technology to MedShr’s real-world medical data. To allow for an even stronger surveillance system, the data can in future be further enriched by ingesting scientific research papers, electronic medical records, and social media.
MedShr’s Early Warning System was awarded third prize of $660k in The Trinity Challenge by an independent panel of world-renowned experts, including Jacqueline Miller (Moderna’s senior vice president of infectious diseases), Roopa Dhatt (executive director, women in global health), and Githinji Gitahi (chief executive officer, Amref Health Africa).