Dr. Spyro Mousses, CEO of Systems Oncology, LLC, announced the launch of the Expansive.AI project today at the AIMed Conference in London, UK to an international audience of leaders in artificial intelligence (AI). Systems Oncology, an AI-based biopharmaceutical company, and its partner, Systems Ima
Our Critical Care Datathon, in partnership with MIT Critical Data and Google Cloud, took place at Imperial College London last weekend (08/09/18 - 10/09/18). This datathon was a learning forum where multi-disciplinary teams explored large critical care datasets to answer specific clinical questions.
Machine Learning is being used, to great effect, to enhance the value of medical data in the direct-to-consumer genomics space. The success of 23andMe shows the huge potential of consumer-led genomics analysis for scientific research: they recently used ML to collate 600,000 customers’ personalised
Like most others, I am curious of how AI transcends, takes form and solves problems. However, I am more curious to find out how AI empowers the Batman and Superman of today rather than the forecasted vision to create a Transformer or a Death star in the future. Of the many applications of AI, health
It is estimated that for every five-hospital discharge patient, one patient needs some form of extended treatment for the next 15-30 days. However, more often than not, patients do not avail the required treatment outside the hospital. One major reason for this is that hospitals don’t find financial
The average rural population visiting primary healthcare centers has increased over the years 32884 as of 2016 while the norm is 20000-30000. In addition to primary check, AI and IoT could help doctors perform early diagnosis on other relevant disease states like breast cancer. If we were to even lo
In India, there is an estimated 900,000 practicing Allopathic Doctors. And yet, there’s only 1 doctor for every 1668 people to access. To worsen the problem, close to 75% of the doctors practice at urban agglomerate servicing only 28% population. This leaves an almost near zero cover for 76% of the
The elemental complexity of emergency medical care leads to barriers that must be overcome for meaningful Emergency Medicine Artificial Intelligence (EMAI) to exist. Accurate data extraction is at the core of a successful AI tool. As EMRs mature, the information contained becomes more trusted. The s
Close to half of all hospital-based health care delivered annually in the US is performed in emergency departments (ED), and this fraction is rising [1]. Emergency medicine (EM) physicians must simultaneously care for multiple patients, many of whom are critical, making rapid access to patient and c