Advances in technology have changed the face of healthcare significantly. We have vaccines for every childhood disease, a tribute to preventative medicine. There are more evolved treatments for conditions that once had a high mortality rate. Diagnostics are better than ever before, and early detection saves many lives.
Despite this, quality healthcare is not available to the global population in an equitable manner. Even in first-world countries, not everyone has access to medical care. Costs and health insurance are not affordable for everyone. The current models are becoming unsustainable and cumbersome.
What is needed is to improve the speed and value of healthcare, make systems more efficient and robust, and extend care to all the world’s citizens. This is where artificial intelligence (AI) and robotics come in. Although they will not take the place of healthcare personnel, they can help us to achieve these goals. Here are some examples of how AI and robotics are taking the next leap forward.
Improved Detection
Medical devices that use AI can be worn by patients to monitor heart conditions and provide warnings when action is needed. This has reduced patient mortality rates and allowed for life-saving measures to be taken in time. Sugar levels and blood pressure in at-risk patients can also be followed. These are a few instances of devices that can be worn to track various medical conditions.
Using the Internet of Medical Things (IoMT), patients can be screened as they go about their day by staff who get the information to their desktops. Screening patients in hospitals can be done from a single nurse station, freeing up nurses to take care of those who need it. This can go a long way to addressing the critical shortage of nurses that is being experienced around the world.
Fifty percent of healthy women are misdiagnosed with breast cancer based on mammogram results, and consequently need a biopsy as confirmation, as per the American Cancer Society. AI can interpret these tests with an accuracy of 99% and does so thirty times quicker than traditional diagnostic tools.
Promoting Healthy Lifestyles
IoMT can also be used for apparently healthy people who want to monitor their health. Results can be stored in the Cloud or sent to a mobile device or laptop. Many fitness fanatics are keeping track of their exercise programmes and vital statistics with wearable devices that tell them how far they have walked in a day, and what their blood pressure and pulse rate are. Caregivers have a better understanding of patterns of symptoms in their patients which enables them to prescribe more specific doses and the best medication for a particular person.
These are examples of preventative and proactive medicine at work. Consumers take responsibility for their own health and can be alerted to any signs that they need to see a doctor. These tools have encouraged a health focus in people as opposed to reacting and seeking medical advice when things go wrong. As a result, they make better lifestyle choices that reduce illnesses overall.
Pattern Recognition
AI is capable of recognising patterns. It also has a self-learning component that enables it to keep getting better at doing this. Thus, AI can pick up early symptoms, minute changes in laboratory test results, and other factors. Predictive analytics is used to identify those people more at risk of a certain disease, signs of a worsening of medical conditions in existing patients, responses to medications, lifestyle changes, and even environmental aspects.
Big Data in healthcare enables the management and analysis of loads of data too complex and voluminous for ordinary computers to handle. AI uses machine learning algorithms to process this data. The feedback this provides assists doctors in making better decisions and prioritising patients.
The management of administrative data reduces the workload of support staff in healthcare facilities. This means more salaries are available for critical posts.
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Leading Edge Initiatives Using AI And Robotics
Watson for Health by IMB is an AI system that is able to store such vast quantities of information as to boggle the mind. It can hold the entire world’s medical data, including all symptoms, case studies, medical journals, treatments, and outcomes. Furthermore, it uses cognitive technology to unravel patterns and make accurate diagnoses. Imagine this being accessible to every clinician on the planet and being used to diagnose and treat every patient.
Many people lose their lives every year due to avoidable conditions such as sepsis, which could have been prevented. DeepMind Health technology has partnered with Google Health to combine expertise across the globe to get on top of complex issues. This sharing extends the use of tools such as Cloud storage, data security, app development, and user design and leads to new products for the management of healthcare. AI, systems neuroscience, and machine learning work together to create learning algorithms that simulate the human brain’s neural networks.
Robotics for End of Life Care
The human lifespan has increased across the decades and generations. People are taking longer to die as medicine can prolong life for much longer. Yet, many elderly citizens have conditions that negatively impact their quality of life. Additionally, they are often alone at this stage of their lives.
Robotics can do much to ease the burdens of the end-of-life phase. Humanoid robots powered by AI can simulate human conversations to stave off loneliness and help failing minds recall and retain information. They can remind patients when to take their medicine and monitor what they eat and when they sleep. Thus, these aged citizens can remain independent for much longer.
Much of what has been mentioned here is only the tip of the iceberg. AI is not yet in widespread use. Nor is it accessible to every patient on every continent. However, as these advances continue and with the crisis in healthcare that we face, the solutions will be found in AI and robotics and become the new standard in medicine.
