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Artificial intelligence and the NHS

The intimidating process of medical diagnosis may very well be changing. Theresa May will later today discuss the possibilities of utilising AI as a “new weapon” for the NHS to diagnosis patients with a swifter process that may completely transform the health industry. 

By adapting with AI, the government is aiming to prevent over 22,0000 cancer-related deaths a year by 2033, while also creating hundreds of high-skill science jobs. With this goal in mind, AI may be able to save lives that would otherwise be at risk if undiagnosed and untreated early on in their illness. The experts say that it will also aid in the fight against diabetes, dementia, and heart disease.

"And the development of smart technologies to analyse great quantities of data quickly and with a higher degree of accuracy than is possible by human beings opens up a whole new field of medical research," said May. 

Theresa May wants to see computer algorithms used to create a diverse web of patient’s medical records that can be analysed by NHS AI to note lifestyle and genetics that could possibly foreshadow diseases such as cancer. 


Fine-tuning treatment

The University College London Hospitals has already announced an ambitious three-year partnership with the Alan Turing Institute to use AI to carry out tasks traditionally performed by medical staff, from assigning patient priority to diagnosing illnesses. Their goal seeks to bring the benefits of machine learning which has constantly been envolving including from Machine learning in warehouse, to the NHS and evolve the very way that our healthcare system adapts to the ever-growing health issues of England.  

If the AI is adapted right, the data of thousands of patients will be used by machine learning algorithms to connect what illnesses a patient’s symptoms might correlate to. Hopes are high that the substantial investments in machine learning and artificial intelligence algorithms for the healthcare industry will provide new ways of seeking out possibly terminal diseases, identify those with illnesses, and help to direct patients to the appropriate resources. 

By putting AI in hospitals, it can be utilised so that doctors and medical staff can be better placed to focus on more urgent or specialist tasks. Experts have already been quick to suggest that NHS roles will only grow, not shrink, from this. 

The first goal for the hospital will focus on adapting their accident and emergency department, hopefully boosting their time targets. 

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Published on 22 May 2018

Last updated on 22 May 2018


  • Sigurjon Helgi Kristjansson - 26 May 2018

    A few decades ago, a Dr. asked his secretary to enter a few details onto a computer and assess if it was a computer or a real person she was dealing with. After only about 5 questions, she asked him if "they" could be alone. The questions were in such a friendly manner (unlike many Dr.s today, who lack bedside manner or go O.T.T.), that it made his secretary feel "comfortable" with the computer, and inputting details. A later improvement on this test, was a program that asked questions, and if data was lacking, would bring up comments and questions along the lines of: "Interesting, tell me more?" After only 5 questions, the computer gave output on another terminal, as to what the possibilities were, one of which the Dr.s thought was absurd. After 10 questions the computer had narrowed it down to about 5 possibilities, incl. the absurd one. After 20 questions, the computer made a definite diagnosis of the absurd answer. Because it was a rather rare occurrence, Dr.s dismissed it, but the computer didn't have emotions, and logic dictated that this was the most likely cause for the ailment. The computer was correct. If programmed with enough data, human error can be omitted, as can cases of misdiagnosis and unnecessary invasive examinations and prescription of expensive medication, which can cause a great deal of expenditure for the NHS as well as the patients, not to mention the emotional trauma and physical and emotional discomfort.


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