How AI and deep learning are being used in healthcare?
Artificial intelligence, or AI, has become increasingly common in modern life and powers everything from digital household assistants like Alexa to much more complicated networks that help BP make the production and refining of oil and gas much safer. Incredible advances are constantly being made in the areas of AI and machine learning, such as deep learning, which allows computers to analyze data with incredible speed and precision.
Deep learning makes use of a layered algorithmic architecture to analyse data. Data is filtered through a cascade of layers that learn from the results of the previous layer. This means deep learning models will become increasingly accurate as they process more data.
Artificial intelligence and deep learning are being used by healthcare organisations in a variety of ways. AI can diagnose patient data more accurately and quickly, perform new research into drugs and assist with complicated surgery. Here are some of the amazing ways artificial intelligence and deep learning is being used in healthcare:
Improved Diagnosis
Diagnosis is one of the areas with the most potential in regards to artificial intelligence. AI could drastically improve a patient's chances of early detection of illnesses by detecting patterns across a patient’s records and using that data to make predictions. A significant amount of healthcare start-ups are focusing on improving diagnosis with AI.
Artificial intelligence is capable of making an accurate, reliable and early diagnosis that is based on predictions and patients symptoms. Due to the vast amount of data that an AI is capable of analysing AIs are often outperforming doctors in diagnosis.
Babylon Health, a subscription service based in the UK, provides an AI chatbot that patients can use to ask medical questions, receive advice and get diagnosed. The app’s developers claim that it is as accurate as a human doctor.
AI can detect disease much earlier than a regular doctor can by detecting changes in health that can indicate a disease, like cancer, long before a patient will start to show symptoms that a physician can detect. This is not only better for the patient’s prognosis but also makes treatment easier and less expensive.
Drug Research
Researching and creating new drugs is incredibly complex and time-consuming and often doesn’t actually reach patients. AI and deep learning can make a massive contribution to drug research by cutting the time and cost that goes into developing new medicine.
The layered algorithms we described earlier can analyse large groups of biological and chemical data much quicker than a human can. This data can be used to discover potential drug candidates that can treat a certain disease. These algorithms are capable of predicting the effectiveness and side effects of a potential new drug.
TwoXAR and Atomwise are two companies that use AI and deep learning to research and discover new drugs much more quickly and affordable than current methods.
AI Assisted Surgery
Artificial intelligence has a big role to play in modern surgery in a variety of ways and can improve the outcome of surgery, especially in complex surgical procedures.
Digital Surgery has the world’s largest collection of surgical intelligence that can be used to train surgeons. Using this library of information, surgeons can train to make fewer errors and perform safer surgery.
AI can also assist surgeons during the surgery itself. By using data from previous surgeries, AIs can tell a surgeon the best way to perform surgery and make real-time recommendations. Artificial intelligence can also be used alongside surgical robots for incredibly precise procedures that would be too difficult for a human surgeon. The robot would be controlled by the surgeon who would use it to perform precise movements, whilst the AI would respond to any tremors and stabilise them.
Image Analysis
Currently, image analysis is done by medical professionals by examining and comparing scans. It’s a necessary but time-consuming process. However, AI and machine learning could significantly speed up the process by examining scans up to 1000 times faster than a doctor could.This could let patients receive life-saving treatment much more quickly or allow surgeons to see how a procedure is going in real time by using an AI to analyse scans.
Personalised Treatment
Currently, the huge amount of data that is used by doctors to create a treatment plan for patients makes it difficult to provide anything other than a generalised treatment plan. However, patients can react differently to treatment and their illness can progress in different ways which means this style of trial and error treatment can make all the difference to a patient’s outcome.
Artificial intelligence is able to analyse a patient’s data and use its resource of research data to predict how an individual patient would respond to a certain style of treatment which would allow doctors to create a personalised treatment plan that would improve a patient’s outcome to treatment.
Administration
Artificial intelligence has the potential to save healthcare administration a lot of time and money by assisting with tasks like filling in patients records, prescribing medication or filling in other paperwork. Doctors and nurses could make use of voice to text transcription of vital information and the automation of other mundane tasks to make their administration much more efficient.
These are just some of the ways that artificial intelligence and deep learning are changing how we receive healthcare. As new developments are made in AI and machine learning we will no doubt see many more advancements that will continue to improve diagnosis and treatment of patients and will help medical professionals provide the highest possible quality care to patients.
This post was contributed by Annabelle Lopez, a contributor at UKS Mobility.