Artificial Intelligence (AI)in healthcare


The milestones covered by Artificial Intelligence (AI)in healthcare are expected to change in the way the healthcare industry is looked at. The level of acceleration of growth of Artificial Intelligence in healthcare has been pretty quick and is currently unpredictable. Key clinical healthcare Artificial Intelligence (AI) apps can create $150 billion in annual savings for the United States healthcare economy by 2026

Many industries have been disrupted by the arrival of new technologies in the Information Age. Healthcare is no different. Particularly in the case of automation, machine learning, and artificial intelligence (AI), doctors, hospitals, insurance companies, and industries with ties to healthcare have all been impacted in many cases in more positive, considerable ways than other industries.

There is also a major change in the way patients are treated. Doctors no longer need to worry about drug overdose or wrong combinations or allergies because this information will all be saved in the cloud, to be trusted on and operated upon at the right time.

About 86% of healthcare provider organizations, life science companies, and technology vendors to healthcare are using Artificial Intelligence in healthcare applications. By 2020, these organizations will spend an average of $54 million on artificial intelligence (AI) projects.

Artificial Intelligence in healthcare aims to mimic human intellectual functions in treatment. It is bringing a model shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of Artificial intelligence (AI) in healthcare applications and discuss its future. Artificial intelligence (AI) healthcare can be applied to various types of healthcare data (structured and unstructured).

Popular Artificial intelligence (AI) techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing for unstructured data. Major disease areas that use Artificial intelligence (AI) in healthcare tools include cancer, neurology, and cardiology. We then review in more details the Artificial intelligence (AI) in healthcare applications in stroke, in the three major areas of early detection and diagnosis, treatment, as well as outcome prediction and prognosis evaluation. We conclude with a discussion about pioneer AI systems, such as IBM Watson, and hurdles for real-life deployment of Artificial intelligence (AI).

Recently Artificial intelligence (AI) in healthcare techniques have sent vast waves across the industry, even fuelling an active discussion of whether through Artificial intelligence (AI) doctors will eventually replace human physicians in the future. We believe that human physicians will not be replaced by machines in the foreseeable future, but Artificial intelligence (AI) in healthcare can definitely assist physicians to make better clinical decisions, clinical decision support or even replace human judgment in certain functional areas of healthcare (radiology).

While there is still much to overcome to achieve Artificial intelligence (AI)-dependent health care, most notably data privacy concerns and fears of mismanaged care due to machine error and lack of human oversight, there is sufficient potential that governments, tech companies, and healthcare providers are willing to invest and test out Artificial intelligence (AI)-powered tools and solutions.

With an estimated value of $40 billion to Artificial Intelligence (AI) in healthcare, robots can analyze data from pre-op medical records to guide a surgeon’s instrument during surgery, which can lead to a 21% reduction in a patient’s hospital stay. Robot-assisted surgery is considered “minimally disturbing” so patients won’t need to heal from large cuts. Via artificial intelligence (AI) in healthcare, robots can use data from past operations to inform new surgical techniques. The positive results are indeed promising. One study that involved 379 orthopedic patients found that Artificial intelligence (AI)-assisted robotic procedure resulted in five times fewer complications compared to surgeons operating alone.

A robot was used on an eye surgery for the first time, and the most advanced surgical robot, the Da Vinci allows doctors to perform complex procedures with greater control than conventional approaches. Heart surgeons are assisted Heart lander, a minor robot that enters a small cut on the chest to perform mapping and therapy over the surface of the heart.

From interacting with patients to directing patients to the most effective care setting, virtual nursing assistants could save the healthcare industry $20 billion annually. Since virtual nurses are available 24/7, they can answer questions, monitor patients and provide quick answers. Most applications of virtual nursing assistants today allow for more regular communication between patients and care providers between office visits to prevent hospital readmission or unnecessary hospital visits. Care Angel’s virtual nurse assistant can even provide wellness checks through voice and Artificial intelligence (AI) in healthcare.

Conditions like diabetes, cholesterol, fertility issues, and cardiac health are managed by regular monitoring and lifestyle changes. Chronic conditions are the single- largest burden on healthcare systems globally. Connected POC devices help generate a lot of data about the user’s body parameters. This can be combined with lifestyle information like food habits, exercise, by an Artificial intelligence (AI) algorithm to help manage the conditions and adjust the dosage of medication.

Some of the initiatives of Microsoft India in healthcare include a Microsoft Intelligent Network for Eye care (MINE) project where the company is working the government of Telangana for its Rashtriya Bal Swasthya Karyakram. The state government has adopted the MINE an Artificial intelligence (AI) platform to reduce avoidable blindness.