Artificial intelligence (AI) is applied throughout healthcare: from administration to patient interaction and medical research, treatment. Specially, the uses of Artificial intelligence in disease diagnosis are really helpful and important.
What is AI in Healthcare?
AI in healthcare is the application of artificial intelligence to medical services and the management or delivery of medical services. Machine learning (ML), large and often unstructured data sets, advanced sensors, natural language processing (NLP), and robotics are used in a growing number of healthcare sectors
While the use of AI in healthcare is just getting started, it is being used more and more. Gartner has estimated that global healthcare IT spending will reach $140 billion by 2021, with companies citing AI and Robotic Process Automation (RPA) as top spending priorities. Here are 5 of the top areas where AI use cases are being developed and deployed in healthcare today.
Aiding in the accurate diagnosis
Hekate cooperates with a team of doctors in Da Nang City to apply Artificial Intelligence in the diagnosis of cerebrovascular occlusive diseases, cerebral aneurysms, including prediction, screening, analysis and interpretation of episodes. huge data from X-ray images. This can be used to gain useful insights and predictions, allowing for a better understanding of disease progression, thus facilitating early disease detection and prompt treatment.
Support in Clinical Decisions
It is obviously imperative that healthcare professionals consider all relevant information when diagnosing patients. As a result, it leads to searching through various complicated unstructured notes kept in medical records. If there is a mistake in keeping even one relevant fact in mind, a patient’s life could be endangered. Support for Natural Language Processing (NLP) makes it easier for doctors to parse all relevant information from patient reports.
Artificial intelligence has the ability to store and process large datasets that can provide knowledge bases and facilitate investigation and recommendation individually for each patient, thereby improving clinical decision support. Doctors can rely on this technology to identify risk factors through unstructured notes. An interesting example of this is IBM’s Watson using AI to predict heart failure.
Enhance Primary Care and Triage through Chatbots
People tend to make appointments with their GP at the slightest medical threat or problem, which can often turn out to be a false alarm or something that can be cured through self-medication. AI helps enable a smooth flow and automation of primary care, allowing physicians to focus on more critical and serious cases.
By saving money on avoidable doctor visits, patients can take advantage of medical chatbots, an AI-powered service, integrated with intelligent algorithms that provide patients with instant answers to all their health-related questions and concerns, while also guiding them in managing possible problems. These chatbots are available 24/7 and have the ability to handle multiple patients simultaneously.
Artificial intelligence and collaborative robots have revolutionized surgery in terms of speed and depth when making delicate incisions. As the robots do not get tired, the problem of fatigue during long and critical procedures is eliminated. AI machines can use data from previous surgeries to develop new surgical methods. The precision of these machines reduces the possibility of accidental or involuntary vibrations or movements during operations.
Virtual nursing assistants
AI systems facilitate virtual nursing assistants who can perform a variety of tasks, from talking to patients to directing them to the best and most effective unit of care. These virtual nurses are available 24/7 and can answer questions, screen patients, and provide immediate solutions. Currently, many AI-powered virtual nursing applications enable more regular interactions between patients and caregivers between office visits to avoid unnecessary hospital visits.
Minimizing the burden of EHR use
Electronic health records have played a vital role in healthcare’s journey to digitization, but the shift has created a number of problems associated with cognitive overload, endless documentation, and user burnout. EHR developers have started using artificial intelligence to create more intuitive interfaces and automate some routine processes that consume a large part of the user’s time.
While speech recognition and dictation help improve the clinical documentation process, natural language processing (NLP) tools may not go that far. AI can also help process routine inbox requests, such as medication refills, and generate notifications. It can also help prioritize tasks that need doctor’s attention, making it easier for users to work with their to-do lists.
While this technology still looms over certain layers of dangers and perils, Artificial Intelligence tools can aid the medical industry in enabling faster service, more accurate diagnosis, and data analytics for detecting trends or any genetic information that would expose someone to a particular disease.
We exist in an era where saving even a couple of minutes can save lives and in these times, Artificial Intelligence and machine learning can be transformative not only for healthcare but for every single patient.