Artificial intelligence has already begun to impact healthcare as it has automated many processes for humans. technologies are becoming increasingly common in business and everyday life and are also used in healthcare. Using AI in healthcare means added assistance in many aspects of patient care and administrative tasks. In addition, it could help healthcare providers improve on existing solutions and solve problems faster.
However, AI is already impacting health care surprisingly, and its potential to improve this industry seems endless. So much so that a recent report from Accenture calls AI the most critical technology in health care today!
In the next five years, the health AI market will grow by more than ten times what it is now. From less than 20 healthcare-related AI deals in 2012 to almost 70 by mid-2016, showing growth picking up speed.
Research focusing on AI in healthcare claims AI can diagnose diseases quicker and more accurately than humans. However, it will be long before AI in healthcare can do a wide range of medical tasks that humans do now.
The two most significant advantages of using AI in the medical field are accuracy and efficiency. With that said, let’s look at how it’s already improving health care and how it will continue to do so in the future.
Automated Appointment Scheduling:
Artificial intelligence has already begun to impact healthcare as it has automated many processes for humans. For example, at Kaiser Permanente, the use of AI in healthcare means that patients can book their appointments online 24 hours a day more accurately than ever before.
The benefits of this system are pretty evident across all departments, from patient access to billing and eligibility verification. It also helps eliminate human error and speed up our ability to provide patient services. And doctors can spend more time talking to patients about their medical needs rather than scheduling them.
Computational Drug Discovery and Drug Effectiveness:
Artificial intelligence (AI) is making drug discovery faster and more efficient. This process, called computational drug discovery, uses artificial intelligence to predict which drugs may be effective against certain diseases.
Computational drug discovery can help researchers find promising new treatments more quickly by predicting how a given drug can and will interact with and how it might affect patients. Researchers then use that information to refine their research design before conducting animal studies or clinical trials.
Computational drug discovery uses computer models to predict which compounds may have therapeutic effects on specific diseases. These models simulate chemical interactions within a cell and can produce detailed three-dimensional models of complex molecular pathways. For instance, the way cancer cells interact and react with specific molecules.
Electronic Health Records:
With increased reliance on technology in health care, patients can have their medical records available when they see a doctor or get an appointment at a hospital. With EHRs, doctors can provide faster and more accurate care by accessing all the information about a patient’s care.
In addition, an electronic health record is easily accessible and retrievable, which helps doctors ensure that they are giving patients appropriate treatments. This way, hospitals save money because they don’t have to hire more staff members who would otherwise be retrieving records from filing cabinets and labeling files.
Virtual Nursing Assistants:
The healthcare industry has been struggling with a shortage of nurses for years. Nurses must work 12-hour shifts in many hospitals and simultaneously cover multiple departments. As a result, there’s no time left to provide patients with the individualized attention they deserve.
A virtual nursing assistant can perform more tasks at once and provide better patient care. As a result, nurses can focus on what’s most important: caring for their patients.
Artificial intelligence has many potential benefits in health care. For example, technology can give doctors more time to focus on patients by handling some of the routine work that consumes a large part of their day. It can also increase diagnostic accuracy, leading to fewer mistakes and less need to redo tests. In addition, doctors could use AI to take notes during patient visits and free up time for face-to-face interactions with patients.
However, medical diagnoses often require complex expertise and access to data sets not readily available to most physicians. As AI systems evolve, they may become capable of making decisions that are as good as human experts. Still, they are not yet there, so we should be careful about the data sets available when training algorithms and designing them.
For example, IBM Watson Health could diagnose lung cancer at least as accurately as expert physicians, but only if it had access to an appropriate lung cancer database; without this database, its performance dropped significantly below expert levels.
Artificial intelligence has and will continue to alter how healthcare providers think about diagnosing and treating patients. As AI becomes more sophisticated, it can become a powerful tool for making treatment recommendations based on patients’ needs. For example, AI can make personalized treatment plans by considering genetics, family history, and lifestyle factors.
AI also provides doctors with constant updates on patient progress, meaning they are always up-to-date with treatments and diagnoses. Doctors can also use AI to refer patients to other healthcare providers with expertise in a specific area of medicine or surgery.
Better Coordination Between Healthcare Departments:
Artificial intelligence has already been used in many healthcare areas, including image recognition and data analysis. AI can also help improve coordination between departments. For example, artificial intelligence may monitor a patient’s vital signs and alert a doctor or nurse when something seems off. By using AI to detect patterns in patient behavior, clinicians can predict future events more accurately and make decisions accordingly.
Better coordination between departments means faster and more accurate responses to patient needs, which helps reduce costs and improve the quality of care. By reducing duplicated testing, AI can also help save money and reduce waste in supply chain management. By predicting stock-outs before they happen, supply chains can be made more efficient with fewer shortages and more satisfied customers.
Disease Prediction and Prevention:
The medical field has long been at the forefront of technological innovation. From microscopes to CT scans, healthcare professionals have relied on technology to advance our understanding of disease and provide new treatments and cures.
However, one of the latest innovations in health care is artificial intelligence (AI). AI can predict when someone will get sick, how they will respond to a specific treatment, and even how they will react in certain environments.
One of the best examples of AI in healthcare has been IBM’s Watson, which can ingest data from patient records and previous research and answer doctors’ questions about the diagnosis. As a result, it has helped identify new biomarkers for various diseases, such as cancer.
Watson has also analyzed large amounts of data to find previously undiagnosed disease cases, particularly in low- and middle-income countries. For example, Watson helped identify a new form of leukemia by analyzing several hundred thousand images from biopsies and finding a previously unknown pattern.
This article highlighted how AI has changed and improved healthcare over the past few years, with more exciting developments on the horizon.
Artificial Intelligence (AI) technologies are redefining healthcare, bringing about massive improvements beyond the technology itself. While no single technology will cure healthcare’s challenges, AI can help drive transformative change and make care safer, more effective, and less expensive.