To assist. Not replace.
Enhancing research and diagnosis across the healthcare sector.
In healthcare, the priority in every decision is the patient outcome. But arriving at the best possible outcome for each and every patient involves careful consideration of multiple, often conflicting factors, and is often based on a limited available dataset.
In such circumstances, those at the front line of healthcare provision do an incredible job, but it comes with a heavy emotional, mental, and often physical burden: long hours, high-stress environments and limited resources all play a factor in how effective any medical team can be. Imagine how effective they could be with the support of an almost unlimited supply of medical data and insight, and the predictive power of AI.
The accuracy and speed with which an accurate diagnosis can be reached can obviously have a dramatic bearing on the effectiveness of treatment and ultimately the survivability of many illnesses. This can result in a number of statistical challenges for both healthcare providers and their patients – the effectiveness of treatment and diagnosis can often correlate with the geographic area in which a patient is seen, or the individual experience of their doctor having seen similar cases in the past.
Add to this the fact that diagnosis is often done by the visual examination of symptoms, or by interpreting the visual outputs of various x-rays and scans, which are susceptible to human error, and the case for AI is clear.
Leveraging neural networking to classify, segment and cross-reference images from MRI, CT, ultrasound and other scans, for example, enables swift, accurate identification of symptoms, and removes much of the risk of false-positives.
Additionally, by compiling results from multiple organisations, and across geographic boundaries, doctors are able to easily draw on a vast databank of diagnoses, far beyond their own experience. Taking this a step further, they can use the power of AI to model various treatment options, and make informed, probability based decisions on the right treatment or care pathway for each and every patient.
Furthermore, our unique algorithms facilitate the implementation of i-DPA to streamline your operations, and continually optimise processes, intelligently. This is vital in a fast-paced environment like healthcare, where continual optimisation and improved efficiency could genuinely save lives.
Away from the frontline, healthcare professionals are constantly battling to better understand and mitigate the effects of major disease. Nowhere is this more prominent than in the current battle to understand and control Covid-19.
In the world of epidemiology, understanding infection rates and how they may affect, and be affected by, any number of other socio-economic factors is critical if scientists and governments are to control or prevent the spread of diseases.
In fact, Artificial Intelligence is already playing a key supporting role in the fight against coronavirus. By leveraging AI, we can understand how and where the disease is spreading next, and model the likely scale of any outbreak. This enables hospitals, and other critical services, to be ready in advance to ensure the right facilities are available in the right numbers to deal with patients.
Its powerful data collation and deep learning capabilities also enable AI to understand the massive datasets generated by the country’s testing centres, tracking apps, hospitals and vaccination centres to rapidly understand how the efforts of Government and healthcare professionals have been in mitigating the virus’s impact. This in turn can be used to understand the benefits, or otherwise, of implementing lockdowns or other social measures.
By augmenting human performance, AI has the potential to markedly improve productivity, efficiency, workflow, accuracy and speed, both for physicians and for patients
– Eric Topol, MD, Scripps Research Translational Institute
Healthcare providers are increasingly becoming the targets of cyberattack. Partly because of the perceived vulnerability of ageing legacy software, and partly because of the enormous commercial value that medical information holds. We’ve seen from attacks such as WannaCry, what the potential impact of a cyberattack can be on hospitals and their patients.
In a sprawling IT estate, such as those managed by Hospital Trusts, with almost endless numbers and types of endpoints, operating systems, and dataflows, just understanding the full attack surface, let alone managing and protecting it can be a challenge.
Quantum AI’s intelligent cybersecurity solution enables IT admins and CISOs to better protect both the network infrastructure and the patient data held within. By actively learning and monitoring every area of the network, and understanding the behaviours of applications, devices and users, Quantum builds a ‘DigitalDNA‘ of each, and can automatically flag or restrict access to any device or user acting outside of known ‘norms’.
This dramatically reduces workload for the IT team, provides them with detailed information of any potential threat, and provides them with the information to actively manage those threats swiftly.
Manage the routine tasks by implementing this and leaving it to run for monitoring and re-checking.
A series of capabilities to support people, and complete projects and tasks quickly and accurately.
Allows challenging, mundane, and repetitive tasks to be fully automated, and self-improving, unsupervised.