7 Ways AI is Transforming Healthcare

Artificial Intelligence (AI) is growing faster than ever before and is bringing new solutions to healthcare. This rising industry has created many opportunities for the betterment of medical treatments through the use of various technologies and equipment that can sense, understand, function and learn new things. These new capabilities allow AI to perform specialised medical and administrative tasks in the many divisions of healthcare. According to the World Health Organisation, by 2035, there will be a shortage of 12.9 million medical professionals internationally. AI can respond to the increasing demand by making up for some tasks where staff members are lacking. Listed below are seven ways in which healthcare is being reformed by AI:

1. Increased efficiency

   AI has and is still improving healthcare providers' efficiency levels in many ways. It saves energy, time and effort and has the potential to save approximately $150 billion annually for the US by 2026. Andy Scheuetz, a senior data scientist in Sutter Health said, "Our initial application of deep learning convinced me that these methods have great value to healthcare." But one must keep in mind that AI is only of real use to the general public if it is accessible to them and can be utilised by most, if not all medical professionals. AI in medicine should not just be for the rich and privileged few, rather its core aim should be to provide quality care for the world.

2. Analysing health records

   Data analysis is a dominant aspect of AI. Information is gathered, stored and its history is analysed to enhance current health systems and develop new and improved devices. DeepMind Health, the AI and research department at Google, was recently put in motion and aims to create devices that have the ability to analyse scans and test results to identify at-risk patients and provide a possible solution for them. It has partnered with Moorfields Eye Hospital NHS Foundation Trust to enhance eye treatment. Such a system must learn to factor-in all possible elements at play in a patient's health situation to be able to come to the correct conclusions. Since AI is a system that continuously learns and evolves, it may also be able to teach hospitals and medical professionals about updated techniques that can advance patient care. AI also increases the prospects of having fast and equal access to quality care since it will make technology available in more places and possibly for lower prices.

3. Creating treatment plans

   IBM has developed its Watson for Oncology initiative which is capable of creating reliable and customised treatment plans. This AI has been taught by doctors from Memorial Sloan Kettering, a reputable healthcare organisation, to analyse patients' EMRs and doctors' notes and provide results based on evidence. Watson has the ability to put this data in context to make decisions. It uses Natural Language Processing to comprehend unstructured notes and come to logical conclusions. In this way, oncologists can focus on more important aspects of a patient's visit and choose from the possible treatment options that Watson provides.

4. Helping in repetitive assessments

   Another program that IBM is currently designing is the MedicalSieve, a project aimed at creating a cognitive assistant that can help health professionals in advanced analysis, medical knowledge and decision making in the fields of radiology and cardiology. This AI will be able to comprehend diseases and how they can be determined using various types of scans including CT, X-ray and MRI. Like the name implies, MedicalSieve will act as a filter that removes improbable diagnoses from the equation by identifying anomalies in the scans. This narrows down the possible diagnoses, making it easier for doctors to identify the problem. Such an initiative can decrease the risk of error as a result of eye fatigue, a common issue in radiologists since they examine many scans on a daily basis. This is one of many more initiatives that will help in repetitive assessments.

5. Automated online doctor appointments

   This feature in emerging AI technologies can help the average person in being diagnosed from the comfort of home. Rather than spending long hours waiting in a doctor's office, applications like Babylon provide automated consultations online, basing its diagnosis on the patient's health records. A person can input the symptoms from which they are suffering into the app, which then runs the data against a database of knowledge. After diagnosing the patient, Babylon then provides treatment options, sends your prescription to your house or local pharmacy, prompts the user to take the prescribed medication and follows up on the problem, just like a doctor would. Other ways in which this app can be used is by scheduling an appointment with an online doctor. You can then save your consultation and watch it again later. In this way, ill patients are not forced to leave their houses to wait for hours for a ten minute check-up, and waiting time at medical practices decreases drastically. Online nursing is another AI technology that has recently been introduced to monitor and assist chronically ill patients in between doctor consultations.

6. Deep learning medicine

   This uses AI to study the genetics and genomics to extract meaningful patterns in databases containing genetic information and health records. New technologies are currently being created to allow doctors the ability to know what happens to cells when their DNA is manipulated artificially or naturally by genetic variation.

7. Drug development

   Formulating pharmaceuticals using medical trials is a time and money consuming approach. AI allows drug developers to produce new medicine quickly and at a lower price. An example of this is Atomwise, a company that utilises supercomputers in its molecular research to discover treatments for viruses and diseases. Previously, this organisation used AI to conduct a search into already existing pharmaceuticals that could be reconfigured to fight Ebola and discovered two products that can effectively reduce the virus' pathogenicity. This discovery, which would have taken months without AI, was completed in less than a single day.