AI in Healthcare
AI’s involvement in healthcare extends to 8 core areas. They are:
1 . Staying Healthy
Prevention, as they say, is better than cure. AI can help to support lifestyle health choices that can keep people out of the hospital. Through the Internet of Medical Things (IoMT), many people are reaping the benefits of AI-supported health activities daily. The use of AI can also help healthcare professionals discover trends in the daily life of their patients for more tailored counseling and management choices.
2 . Early Detection
Technologies like wearables and other AI-supported devices are finding application in the detection and monitoring of the early signs of heart disease. This is useful to prevent progression to later stages that are more difficult to treat.
Cancer detection at the early stage is becoming more reliable due to AI’s increasing involvement. Mammography, for example, which has a high degree of false positives (i.e., women who do not have cancer being told they have cancer) is becoming more accurate as AI becomes more involved in the review and interpretation of results. Accuracy has been shown to go up to as high as 99% while the speed of result review has been boosted by at least 40 times.
3 . Diagnosis
The integration of AI into X-ray and MRI machines is making these machines capable of more than just the internal scanning of the body. Already, AI is showing great promise in diagnosing diseases from radiographic scans.
Google’s DeepMind Health uses machine learning and systems neuroscience to create all-purpose learning algorithms into neural networks that simulate the human brain. Healthcare professionals, researchers, and patients are collaborating with DeepMind Health to find solutions to some of the world’s healthcare challenges.
IBM’s Watson is also proving to be of great benefit in the healthcare sector from its application of cognitive technology to extracting healthcare data/medical information from journals and other sources in an exponentially faster time than a human is capable of. Watson also aids diagnosis through symptoms analysis and case study reviews.
4 . Improve Decision-Making
Whether clinical or administrative decisions, AI can analyze big health data and use predictive analytics to support decision-making for the improvement of the clinical state of a patient or the hospital's administrative state.
5 . Treatment
Beyond the obvious benefits of AI in preventive measures, AI has also been used to great success in treatment modalities. A few of those are as follow:
5.1 . Robotic Surgery
In 1985, Arthrobot became the first robot to assist surgery. It helped to position the patient’s leg during the surgery.
Surgery is a very delicate art because of the high degree of precision it requires. Robots are already helping surgeons perform some of their procedures, but they remain a long way from being able to carry out surgeries on their own. In 2000, the Food and Drug Administration (FDA) approved a robotic surgical system called the da Vinci surgical system. This name was given to it because of the work done by Leonardo da Vinci in studying human anatomy. The da Vinci surgical system has now become one of the most widely used. In 2012, it was used in an estimated 200,000 surgeries.
In 2017, the first super-microsurgery to be completed by robot hands was done by a robotic system developed by the company Microsure for an operation on a patient with lymphoedema. The procedure involves the suturing of vessels as small as 0.3 millimeters. The robotic hands aided the high-precision maneuvering required for the surgery.
Some of the advantages of the use of robots for surgeries include smaller cutting sites, lesser blood loss, faster healing time which can help reduce the length of hospital stay, and the need for pain medication. It can also help surgeons who might have some form of shaky hands. CyberKnife is also a robot surgery system that can help to target cancer cells with radiation.
5.2 . Bionics
Bionics is all about the application of biological methods found in nature to the design of engineering systems. For some time, the options available to people who lost their limbs were limited but now researchers are developing more sophisticated prosthetics that can do more than just fill the space where the missing limb should be. This is where bionic limbs fit in. There is a bionic limb on the market now, Ossur’s Symbionic Leg. This bionic limb can read changes in body position and help with swinging the foot. It also helps a user stay stable and not fall after tripping.
5.3 . Exoskeletons
An exoskeleton is an external skeleton that protects an animal. It can be found in insects and some other animals like crabs. In humans, it is a wearable robot that may help people who have suffered spinal cord injuries or strokes. They work by noting changes in the body position while the motor system moves to flex the hips and knees.
The earliest recorded exoskeleton was designed by a Russian engineer, Nicholass Yagn. Later in the 1960s, the first exoskeleton that could move along with a human’s movements was developed. It was called Hardiman and was the result of the joint efforts of General Electric and the United States army. The Ekso GT, developed by Ekso Bionics, is the first exoskeleton to be approved by the FDA. Some others have been developed since then such as CAPIO and VI-Bot which are general purpose exoskeletons made by the German Research Centre for Artificial Intelligence.
5.4 . Human Connection
The ultimate goal of AI is to be able to mimic human intelligence across various spheres including emotional intelligence. Much of the progress that has been made in AI has been drawn from studying and understanding more about how humans work. The advancement in AI research will therefore help to deepen the understanding of human nature for AI to replicate it. Social robots like we earlier discussed will have to do a lot of human interaction. The ease with which they can do this will come down to how much of human social cues and emotions they understand.
There are virtual therapists like Ellie already helping humans talk about difficult experiences. Researchers developed Ellie at the University of South Carolina to speak with soldiers returning from war zones. Because of the nature of the veterans' psychological difficulties to deal with on returning, they often found it difficult to speak with regular therapists. With Ellie, the research has shown that the soldiers were three times more likely to speak to Ellie than a human therapist. This is positive news for helping people who are worried that they might be judged by human therapists.
6 . End-of-Life Care
Improvements across almost all areas of life mean that humans can now live longer than before. A shortage of healthcare workers to cater to the aging population has necessitated introducing AI into end-of-life care. The introduction of AI -especially as humanoid robots- contributes to the reduction in loneliness, the need for hospitalization, and better independence of old people by aiding the performance of tasks and engaging social conversations that help keep aging minds active.
7 . Research
AI can aid healthcare research through document parsing solutions that can search thousands of articles for specific keywords topics to reduce the amount of time spent searching for reference materials. Furthermore, drug research and discovery may be sped up by AI.
8 . Training
The journey to becoming an expert or specialist healthcare professional is also an area where AI has extended its reach. AI can create realistic simulations better than traditional computer algorithms. Furthermore, due to advances in natural language processing, AI can search a large database of scenarios and clinical situations to adapt questions or provide directions to trainees on a scale and speed that humans cannot. Even more fascinating is the personalization that AI can bring to the training. By storing the responses of the trainee, the learning structure can be better tailored to match the trainee’s learning speed or level.
AI-powered training is also not limited by physical barriers. Learning materials can be accessed at any point in time. The utility of AI in healthcare can be further illustrated by the massive role it is playing in the COVID-19 crisis. AI solutions have been deployed for contact tracing of infected people, diagnosis (through the reading of radiological scans), symptom alert (through fever detection technologies), information verification (by combating the spread of misinformation on social media platforms), vaccine development software, etc.