The market value of AI in the healthcare industry is expected to reach 6 6.6 billion by 2021. Artificial intelligence is growing in popularity in various industries. Most of us associate AI with robots, Alexa and self-driving cars.
But AI is so much more than that. AI professionals see this as a revolutionary technology that benefits many industries.
The impact of AI on the health care sector is truly life-changing. It offers innovations in clinical operations, drug development, surgery, and data management. AI technology is also rapidly entering hospitals.
AI applications are concentrated in three major investment fields: digitization, engagement, and diagnostics.
Looking at some examples of artificial intelligence in health care, it is clear that there are tremendous advances in the inclusion of AI in medical services.
Let’s explore some amazing applications of AI that revolutionize health care.
Nothing is more exciting than AI robots. However, these are not human-like droids from sci-fi films. We are talking complex and intelligent machines designed for specific tasks.
In2017, a robot in China passed a medical licensing test using its AI brain. the same year, the first semi-automated surgical robot was used to stitch narrow blood vessels up to 0.03 mm.
AI algorithms diagnose diseases faster and more accurately than physicians. They are particularly successful in detecting diseases from image-based test results.
Late last year, Google’s DeepMind trained a neural network to accurately diagnose 50 types of eye diseases by analyzing 3D rental scans. It shows how effective AI technology can be in detecting real anomalies.
Effective treatment of cancer depends on early detection and prevention. Some types of cancer, such as various types of melanoma, are difficult to detect at an early stage.
AI algorithms can scan and analyze biopsy images, and MRI scans 1,000 times faster than doctors. Algorithms can confirm with an accuracy rate of 87%. Diagnosis errors and delays are becoming a thing of the past.
Accurate medication refers to delivering the right treatment depending on the patient’s symptoms and behavior. Equally necessary to correct the diagnosis is the appropriate treatment.
This will most likely mean accurate prescription and recovery routines for the best outcome.
The exact amount of medicine depends on the interpretation of vast volumes of data. Patient data is used in determining the most effective medication. The data includes treatment history, limitations, hereditary characteristics, and lifestyle.
Data organization becomes a robust suite for machine learning and AI algorithms. AI-powered data management systems seamlessly store and manage large amounts of data to create meaningful resolutions and expectations.
Hospitals and other health care facilities collect a lot of information from their patients. The data ends up sitting on a hard drive or in a file cabinet. AI pharmaceutical systems can browse through these archives, helping physicians create specific medicines for individual patients.
AI prescription systems are now equipped to deal with adherence to medical prescriptions. They do this by studying the patient’s medical history and determining the possibility of taking the medication as prescribed by the patient.
Development Sustainable development is a tedious venture that takes years and thousands of failed attempts. The process can cost billions of dollars to medical researchers. Of the 5,000 drugs that begin pre-clinical trials, only five are involved in human testing. And only one in five can go to pharmacies.
Many cement lenders such as Sanofi and Pfizer are partnering with tech companies IBM and Google.
They are already tech professionals investing in AI technology. The idea is to build a drug discovery program using deep learning and AI. The results are already paying off.
Drug discovery is now data-driven, rather than the traditional trial-and-error approach. Current medicine can provide intelligent simulations of improved remedies through the analysis of patients and pathogens.
Researchers have been able to divert existing drugs to combat new infections. Thanks to AI research platforms, this is a process that takes days, not months or years.
Personal Health Assistants
A daily example of artificial intelligence in health care is personal health monitoring.
Thanks to the Internet of Medical Things (IoMT) and advanced AI, there is a host of consumer-oriented products to promote better health. Over the past few years, we’ve seen mobile apps, wearables and discrete monitors that constantly collect data and check vital resources.
These gadgets use data to recommend. This is an attempt to resolve any manipulations. Most of these devices store data locally or online. Data can be retrieved and used by medical professionals as a medical report.
Adopting Artificial Intelligence In Health Care
The AI is right here. It does not replace doctors with machines but works with them. The goal is to achieve affordable and effective health care services. Being a relatively new technology in health care, AI still has a long way to go, but progress is impressive.
We can expect improvements and new applications as this amazing technology progresses with time. The improvements will be made not only in the health care industry but also in other sectors.