UK artificial intelligence healthcare pioneer helps fight against Ebola and other deadly viruses


May 27, 2015


Advanced technology could help save lives and halt spread of disease in the UK and abroad

London – 27th May 2015 – UK artificial intelligence pioneer Deontics has developed a breakthrough approach in the treatment of Ebola and similar illnesses that could save lives and halt the spread of disease.

The current epidemic sweeping across the West African region has now killed five times more than all other known ebola outbreaks combined. And whilst cases are levelling off, the danger still remains. Several healthcare workers returned to the UK in March after exposure to the virus, and one military healthcare worker tested positive.

In response, Deontics, a medical artificial intelligence spinout of the University of Oxford, University College London and Cancer Research UK, has used its advanced software to give doctors the ability to view guidance on the best treatment possible for Ebola and other deadly viral haemorrhagic fevers (VHF) when seeing those returning to the UK from areas at risk. Deontics is now looking to extend this capability by producing tools for use by doctors on the ground to treat Ebola patients in West Africa.

“Global health issues such as Ebola are a constant threat that needs a global response, and software such as ours can have the required impact. Our technology incorporates and deploys the clinical logic of the experts in the field to help those treating patients to make the right clinical decisions that can save lives” says Dr. Guy-Wood-Gush, CEO of Deontics.

Deontics’ advanced systems put the UK’s viral haemorrhagic fever: ACDP algorithm and guidance on management of patients guidance from Public Health England and the Department of Health on how to deal with such conditions, directly onto mobile devices and relates the relevant passages to the specific patient helping busy doctors make the right clinical decisions. Doctors can use this to help them provide the highest standards of care in a systematic way, which can reduce the chance of medical errors, disease spread and death.

The guidance is also applicable to staff in hospitals, ambulances, and public health, who are all at threat of exposure to such viral diseases. Using Deontics technology they can access best practice in dealing with VHF quickly and easily at the point of care.

As well as helping tackle Ebola, Deontics software is being used in many areas of healthcare e.g. cardiovascular disease, diabetes, common cancer treatment to reduce unwarranted variability in clinical practice.

The technology is already in use in hospitals in the US and UK and Deontics expects to extend the use of its systems both in these markets and around the world.

For more information on clinical pathways and artificial intelligence for healthcare contact Guy Wood-Gush on guy.wood-gush@deontics.com or visit the Deontics website.

About Deontics
Deontics provides personalised clinical decision support software that is the result of long-term academic research in medical artificial intelligence originating at Carnegie Mellon University, and subsequently developed at the Medical Research Council, University of Oxford, University College London and Cancer Research UK.

Deontics was founded to incorporate concepts rooted in cognitive science, artificial intelligence and medical informatics into day-to-day clinical decision making in order to improve the quality of medical care in the UK and throughout the world.

Deontics provides clinically-led artificial intelligence for healthcare providers that delivers personalised clinical decision support for quality patient outcomes. A clinical ‘sat nav’ for personalised care, it integrates clinical good practice at national and local level with individual patient information directly into the patient pathway in a visually effective user interface. Use of Deontics systems throughout a network of hospitals and primary care clinicians can greatly enhance the quality of integrated care as well as the quality of individual specific clinical decisions.