Artificial intelligence (AI) is becoming one of the strongest tools available to those who work in healthcare.
The software is being used all over hospitals. Scientists are using it to create new treatments while GPs are using it to reduce their workload.
Here, Health Tech World takes a look at how machine learning is being applied across the healthcare industry and changing the lives of patients.
One relatively new use for artificial intelligence has been using it to develop undiscovered drugs to treat a variety of conditions.
A number of companies have spotted its potential and are now rolling out multiple projects using the technology.
UK firm Exscientia is one of the global leaders in this field, having already designed two successful treatments that were solely designed using AI.
They currently have over 20 similar projects underway with a potential treatment for Alzheimer’s recently entering Phase I clinical trials.
The company has more than doubled in size over the past after securing over US$500 million in funding to help its development.
As it is the biggest disease affecting the world right now, it was only a matter of time before academics began looking at the potential AI can have regarding COVID-19.
Although treatments for the virus are still in their early stages, the diagnosis process has been improved using similar technologies.
NHSX recently created an algorithm that is being used to make a clinical decision on people in a hospital setting who have not been able to get a test.
Through the comparison of over 50,000 patient scans from the National COVID-19 Chest Imaging Database (NCCID), clinicians can effectively diagnose a patient.
When it comes to treatments Ananth Krishnan, chief technology officer at TCS, said there are huge possibilities for AI to thrive in this area when writing for Health Tech World.
“The potential for this goes far beyond finding a vaccine for COVID-19,” he said. “The future of healthcare is well and truly shaping up in front of our very eyes and it’s clear that AI has an important role to play in it.”
Another condition that machine learning has made great strides with is cancer.
One of the most common forms of this disease is testicular cancer, with chemotherapy nearly always being used to treat this.
Many patients respond differently from this, with researchers from Denmark creating a system that detects which patients are at the highest risk of developing debilitating side effects from the treatment.
It was able to successfully identify over 90 per cent of patients who were at low risk from developing nephrotoxicity.
Scientists from the University of Leeds created a similar algorithm for elderly bowel cancer patients, assessing their levels of two key proteins which dictate how a patient will respond to chemotherapy.
The same technologies are also being used to create treatments for the disease, with an Innovate UK-backed collaboration using AI to look at future drugs for lung cancer.
The market for restoring limb function is huge and is only being helped through new AI technologies.
Machine learning can help develop devices that read and store data from the brain’s electrical signals, allowing it to adapt to how a person moves.
The University of California is helping pioneer this, with its AI-assisted device that is placed on the forearm is able to take in this information and recognise a person’s hand gestures.
Users begin slowly by making gestures one by one with the hardware constantly updating itself, eventually allowing a much smoother experience.
Discovering new drugs is not always the best solution when it comes to treating certain conditions as researchers from Ohio State University are investigating.
Through processing large amounts of data, scientists are looking to find out more about current drugs on the market to see if they can help manage diseases that they are not currently prescribed for.
The research is predominantly looking at discovering new medication to treat heart disease, with 1.2 million sets of patient data being used by the software.
However researchers have not ruled out the possibility of finding new purposes for a host of other conditions.