Artificial Intelligence: the new healthcare algorithm

Kulveer Singh|26th September 2016

Artificial Intelligence (AI) is the science and engineering of making intelligent machines, and the art of using computers to understand human intelligence. When it comes to healthcare, AI can bring about radical changes to the way doctors and physicians access, communicate, and interact with patient data. Crucially, this can result in improved patient outcomes and even the possibility of using an individual patient’s history - such as previous illnesses, allergies or even genetic makeup - to predict their exact treatment requirements.

Associate Medical Copywriter Kulveer Singh explains how the introduction of AI can change the landscape of healthcare, why it’s an exciting time for the development of new technologies, and the challenges that implementing new AI may pose.

Better than humans? There’s proof!

In 2011, IBM’s supercomputer WATSON competed against and obliterated a long-term game show champion. All this, despite the general thought that computer programmes were unable to understand natural language, puns, red herrings, and to simply unpack the meaning behind game show questions.

With its ability to use natural language capabilities, hypothesis generation, and evidence-based learning, IBM WATSON has made the switch to healthcare and can support physicians in key decision-making processes. For example, an oncologist can use WATSON to assist in diagnosing and treating cancer patients. First, they might pose a query to the system, describing symptoms and other related factors (e.g. a patient has been suffering from severe and unexplained tiredness). WATSON begins by identifying the key pieces of information before mining through patient-related data to find relevant facts about family history, current medications, and other existing conditions. It combines this information with current findings from oncology clinical tests, doctors’ notes, treatment guidelines, instrument data, and scientific literature. It then examines these sources before forming hypotheses and testing them. WATSON will then provide a list of possible diagnoses with an accompanying score that indicates the level of confidence for each hypothesis. This contextual analysis allows WATSON to address complex problems, helping the doctor make more informed and accurate decisions.

Even Google with their DeepMind Health AI technology, have entered into the first NHS research project investigating how machine learning can help analyse ophthalmic scans, leading to earlier detection and intervention for patients with macular deterioration.

Bringing technology to the doctor

The problem

A patient enters a clinic with a real problem. The doctor, with his years of experience, doesn’t recognise the symptoms and is completely at a loss as to how to treat. The patient doesn’t have infinite time, and the situation could worsen very quickly.

The solution

The doctor uses Modernizing Medicine, a database tool that he can scroll through, looks for treatment options for the patient’s rare condition, and writes the appropriate prescription - all in seconds.

The benefit

AI can help eliminate human error and wasted time, and gives the physician a whole host of options at the click of a button. Tools like Modernizing Medicine in the US take information from over 14 million patient visits, and its AI has the ability to streamline treatment options and suggest the most beneficial or most commonly used treatment for each individual patient case.

Modernizing Medicine has improved treatment protocols across many disease areas. In rheumatology, the platform gives rheumatologists the option of having a virtual exam room to cover common complaints, diagnoses, and develop treatment plans for individual diagnoses. 3D-mapping of the body also allows rheumatologists to document patient findings with ease and precision.

AI – a breadth of capabilities

As AI is able to sift through enormous amounts of information at high speed, this brings new hope to the field of research and development (R&D). The efficiency and comparative algorithms included within AI will open the door to tailored and effective drug discovery processes with experts highlighting that it will help bring down long term R&D costs. With the advantage of modern day computers having increased storage and processing power, AI will surely be incorporated into a wide range of areas within the years to come:

  • Medical imaging and diagnostics
  • Virtual assistants
  • Drug safety management
  • Drug discovery
  • A&E/ER and hospital monitoring

Will the machines take over?

The obvious benefits of AI are that they reduce medical error, improve management of patient health, and facilitate faster drug discovery processes. However, one of the biggest factors in the healthcare industry considering implementing AI lies in its cost-effectiveness (i.e. the reduction of human capital).

Doctors fear they will lose their jobs, and with increasingly more companies showing initiative in this field, the role of the physician could become obsolete.

Early AI companies recognise the importance of physician input and are developing their technologies with this in mind – to involve medical professionalsat every point in the disease management pathway.


Rather than replace doctors, this form of augmented AI will help to advance their capabilities, and in the process, bridge the gap between human and computer interfaces; giving doctors the platform to express their opinions to make confident and logical decisions. Together, healthcare and Artificial Intelligence can make a real difference in treating patients effectively.


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