Novel health conditions, as well as increasing expectations from healthcare, have contributed to a technological revolution inside the industry, and medical AI is its cornerstone. What is AI in healthcare, and how does it transform the industry? Let’s find out!
AI in healthcare is the emulation of human cognition and reasoning by complex algorithms in order to automate, scale and enhance processing, analysis, interpretation and comprehension of healthcare data and augment human activity.
By relying heavily on machine learning and deep learning, AI quickly and accurately handles big amounts of data, provides contextual relevance, reduces human error and makes reliable decisions.
AI disrupts the healthcare industry and revolutionizes it by redefining the quality of medical services: better care outcomes, higher quality of life for the patients, higher medical employee efficiency, streamlined workflows and protection from cybercrime.
Also, AI cuts down costs — Accenture predicts that it will help the US healthcare sector save $150 billion by 2026. In the face of increasing demand for medical workers — the World Health Organization estimates it to reach 80.2 million by 2030 — AI takes over a variety of tasks, which reduces labor demand and workload.
Let’s look at the way in which AI revolutionizes digital health and focus on real-life examples of how AI and healthcare work in synergy.
|Read also: The Ultimate Guide to Enterprise AI|
1. Personalized Diagnosing and Treatment
Clinical decision-making has been the key focus of AI since the 1970s, and still, AI in medical diagnostics and decision-making is one of the top use cases.
Unlike humans, AI can process large amounts of data in a short time, provide high reliability and speed of diagnosing and consider secondary conditions, such as genetics, lifestyle and environment. The simultaneous analysis of a myriad of factors allows AI to identify early symptoms that humans can overlook, which improves the quality of diagnosing and increases the number of early detection cases.
The American Cancer Society states that the use of artificial intelligence enables mammogram analysis that is 99% reliable and 30 times faster, significantly improving care outcomes.
Microsoft Azure Cognitive Services, IBM’s Watson and Google’s DeepMind Health are good examples of how AI can help clinical decision-making. They use cognitive services, natural language processing and machine learning algorithms to replicate human reasoning and go beyond its capabilities. Intel’s startup Lumiata created an AI-based platform that identifies patients who are at risk and creates treatment options for them.
In addition to advanced diagnosing, AI health solutions enable outstanding care management, coordinated treatment plans and higher patient engagement. With artificial intelligence, caregivers treat the specific patient, not the disease, which creates the foundation for personalized medicine.
For example, Microsoft’s Project Hanover provides a matching solution that selects the most effective drugs for specific cancer cases.
|Read also: The Importance of Data Collection in Healthcare|
2. All-Seeing Medical Imaging
AI not only enables the analysis of large amounts of data but also helps analyze medical images, such as X-ray, CT and MRI images and others. Human error and misinterpretations may cause professionals to overlook critical data, which negatively affects care outcomes and patient conditions and may even threaten the patient’s life.
Artificial intelligence in medical imaging is based on an extensive historical database, which enables faster, more accurate image recognition and diagnosing, so that no detail is overlooked.
Zebra Medical Vision is a company that trains neural networks to detect unusual conditions in radiology scans. Recently, it has developed and patented an AI solution that helps detect and quantify COVID-19 on chest CTs.
3. High-Precision Surgery
Today, healthcare providers make the most use of robots: machines enhance and extend the physical abilities of surgeons. In most cases, surgeons manage robotic arms, but sometimes machines perform operations on their own. Robotics is already widely used in gynecological, urological, neck and head surgery.
In certain cases, human surgeons can’t compare to their robot colleagues — when it comes to the sharpness of sight, for example, or to the capability to make precise, minuscule incisions. Also, this innovation helps address the human-factor aspect — fatigue, fumbling fingers or disconcerting emotions, all of which may interfere with the surgery.
4. Uncrewed Patient Assistance
It has been quite a while since surgeons started including robots in operating rooms. Recently, AI-powered robots have worked more closely with humans and have embraced more routine patient management activities.
Nursing. Nurses perform many time-intensive tasks, such as blood tests, vital sign monitoring, treatment procedures and more. Modern robots can handle many of these tasks, and will soon allow medical institutions to free up the nurses so that they can focus on their patients instead.
Physical assistance. Robots perform tasks that involve patient care, which includes lifting bed-ridden patients to change the bedding or feeding people with disabilities. Some robots are created to nurse visually impaired, elderly, paraplegic and other patients. AI-powered exoskeletons even enable paralyzed people to walk.
Virtual assistance. For patients with mental health conditions, such as Alzheimer’s disease, AI-driven voice bots are essential, as they help them be self-reliant and perform the basic activities of daily living. Patients get individual reminders about these activities so that they are in full control of their lives. For example, Amazon Alexa’s My Carer assists people diagnosed with early-stage dementia.
Virtual consultants. These AI care solutions allow patients to take remediation actions a soon as they have early symptoms and without visiting a doctor. Babylon Health’s chatbot uses speech recognition and an extensive database of diseases to provide possible diagnoses and recommended actions based on the patient’s medical history and symptoms.
5. Omniscient Telehealth
Artificial intelligence in the medical field reduces the need for direct communication between caregivers and patients, as many tasks can be performed remotely.
Wearable telemedicine devices facilitate routine as they allow patients to visit hospitals less often while ensuring that physicians are always aware of their condition. These devices allow caregivers to monitor patients remotely: they keep the track of vital signs and monitor them for the slightest abnormalities that can go unnoticed by humans. If a device spots a symptom of a disease, it alerts caregivers about it, which allows taking quick remediation measures.
Telepresence robots enable patients to communicate with health workers remotely, via videoconferences, instead of having real-life appointments.
Also, AI-powered applications help improve patient participation in their treatment: relevant, contextual content that caregivers provide to them using mobile applications increases engagement and encourages a healthier lifestyle.
6. Streamlined Medical Insurance
In addition to the fact that artificial intelligence helps patients and caregivers, the medical insurance business can also benefit from it. In this industry, much depends on the accuracy of patient clinical record analytics, which is why data processing should be entrusted to smart algorithms.
AI-based systems analyze data more efficiently than humans do: machines can handle more cases in a given time period while covering more dimensions in lifestyles and behavior. This may significantly impact suggested insurance rates. Also, machine learning algorithms help insurers verify claims for their accuracy — a task that saves a lot of effort for insurers and caregivers.
7. Automated Administrative Tasks
The application of artificial intelligence for administrative tasks isn’t so revolutionary as for treatment, diagnosing or patient care, but it still allows caregivers to shift their focus considerably.
Healthcare requires the accurate processing of big amounts of medical data, and hospital workers spend a great deal of time on related activities through conventional medical software and hospital management systems. In this, robotic process automation (RPA) is of great help: it enables quick, patterned processing of documents: millions of medical records, claims, electronic health records (EHRs) and more. Believe it or not, automated medical records not only relieve personnel from performing manually intensive tasks but also improves care outcomes.
Another valuable capability of AI in medicine are chatbots for patient interactions. Although complicated cases are still to be handled by human workers, simple ones, such as making appointments, is an area in which chatbots excel.
8. Time- and Cost-Effective Research
The journey of a drug from discovery to clinical use is long and expensive: it lasts for approximately 12 years and costs a research company millions of dollars.
Recently, R&D labs have implemented AI and machine learning to automate many processes that are essential for the research and development of medicine. It allows labs to save a considerable amount of time, effort and money.
Advance Your Healthcare Services with AI
Although the use of artificial intelligence in healthcare is just gathering momentum, an increasing number of caregivers are arriving at the understanding that the role of AI in healthcare will soon become critical.
We suggest that healthcare providers implement AI as soon as possible to gain a competitive edge. However, the safety and quality of software is the prerequisite, especially when it comes to healthcare, which is why companies should choose a reliable and experienced software development partner.