AI In Healthcare: 5 Things You Need To Know
For a long time, the promise of AI in various applications has been considered fiction but held in high regard secretly. In instances where human ability falls short, scientists have been working round the clock to bring onboard machine intelligence. Today, artificial intelligence applications cut across all key sectors; transformations by AI improves performance and efficiency. According to research done by Accenture, the level of advancement in the use of AI is expected to touch $6.6 billion in 2021.
Healthcare is one of the most time-sensitive industries that has benefitted from advancements in AI. All systems in a typical hospital setting from nursing care, in-patient management, data entry, insurance, and out-patient management have a corresponding AI application. The nature of hospital work is repetitive and that is why it makes sense to automate some of it. AI technology to a large extent is saving the patient time and facilitating the early start of treatment, especially for time-sensitive health complications.
AI is definitely everywhere but it is in healthcare where it has been significant in saving lives. Quite frankly, this new technology now sits at the center of life and death situations. Here are 5 scenarios in the healthcare system where AI has taken over and completely blended in;
Robotic surgery is happening
The invention of robots is the closest invention by scientists to creating a human being. Healthcare is a $40 billion dollar industry and the adoption of AI is expected to bring some of the operational costs down. With a robot, healthcare professionals can remotely analyze data from medical test procedures. Surgeons can guide their instruments to repair internal organs without as much as a small incision; minimum invasion will reduce post-operation hospital stay by up to 21%.
Through AI, can access and view data from past operation procedures to decide on the next course of treatment. In a recent study where 379 participants were involved, patients of orthopedics where AI was used recorded 5 times fewer complications compared to treatment by human techniques.
The most intelligent robot in the eye surgery spheres known simply as the Da Vinci has been aiding doctors in performing sensitive procedures. Heart surgeons too require such advanced robots and they too have one, the Heartlander that corrects heart ailments through a small incision on a patient’s chest.
Nursing care has been automated
Think of everything a nurse does in a health setup and some of these duties are being taken up by AI systems. By reducing the level of contact between patients and health care professionals, the industry could save up to $20 billion per year. The greatest advantage of virtual nursing is that the program is operational throughout; it monitors the progress of patients and gives rapid solutions to health queries.
For those wondering how nursing can be effective without a personal touch, it is important to note that modern systems facilitate regular conversations between patients and healthcare providers.
Clinical diagnosis and analysis is easier with AI
The use of AI to make medical diagnoses is still in the infancy stages. However, ongoing studies have been quite interesting. The most recent study in this field was conducted at Stanford University where researchers sort to establish if an AI algorithm can be used to detect skin, as well as dermatologists, do. The automatic system performed at the same level as human beings!
In another study, an AI systems company in Denmark tested an ongoing program where a computer was made to eavesdrop on an emergency call made by human dispatchers. The system algorithm was able to pick the message, discern the tone of voice and measure these two elements against background noise. The system has so far been able to detect the onset of cardiac arrest with an accuracy of 93%which is 20 points higher than human doctors are capable of.
According to a recent Baidu research, it has been discovered that when deep learning algorithms are put to work in healthcare, the performance is by far better than for humans. Speaking about the great advancements in the UK health center, Prime Minister, Theresa May recently expressed confidence that an AI-driven revolution would aid the treatment and early detection of cancer.
Management of work and administration duties
Another application of AI in healthcare is in the automation of administration work. Saving time required to perform various tasks within a hospital setting is important because it is what ultimately leaves ample time to look after patients. With regards to paperwork, most modern healthcare providers rely on integrated systems to store patient data. Data management systems can now be used to write chart notes, give prescriptions, and order for medical analysis.
The Cleveland Clinic in Ohio is proof of how AI is being used to manage administration work and allocate duties. The facility uses an IBM robot called Watson for data mining so that physicians can provide each patient with an efficient and personalized treatment experience. Watson is a doctor’s companion whose key role is to analyze multiple medical publications to come up with informed treatment plans.
Analyzing medical imagery
With an increased number of people visiting medical facilities for specialized care, it is becoming tedious for human experts to read decipher medical imagery. A team led by MIT scientists recently came up with an AI algorithm that uses machine language to process 3D scans 1,000 times faster than is possible for the best human ability. This advancement makes medical analysis almost real-time and of use to surgeons as a theatre companion. The next step from here is to come up with radiology innovations that do not entirely rely on real tissue removal to test. In addition to saving time and tested human tissue without having to remove it, AI-assisted image analysis could be the answer to providing medical care to rural populations.
The provision of quality healthcare is dependent on a wide range of factors that AI is coming in to solve. Data analysis is particularly interesting in that past medical history is analyzed against genetic data to measure the possibility of various illnesses long before they develop. A crucial element of saving lives in healthcare, timelines with AI are now shorter. This is what every single patient deserves to get from healthcare provision services.