Medical devices are using Artificial Intelligence (AI) and Machine Learning (ML) algorithms to diagnose diseases with a sensitivity and specificity that significantly exceeds doctors. AI is introducing a paradigm shift in healthcare, driven by the increasing availability of healthcare data and the rapid progress of analysis techniques. We analyze the current state of AI applications in healthcare and analyze their future. AI can be applied to several types of health data, such as structured data, which includes classic vector support machine and neural networks, as well as modern deep learning.
Unstructured data can be analyzed with natural language processing. The main areas of disease that use AI tools include cancer, neurology and cardiology. In stroke, AI is used for early detection and diagnosis, treatment, prediction of outcomes and evaluation of prognosis. Pioneering AI systems such as IBM Watson are helping to overcome the obstacles to deploying AI in real life.
Data mining allows health service providers to have a better doctor-patient relationship and, in turn, provide better patient care. Machine learning has altered the health system by allowing the use of artificial intelligence in medical diagnosis and treatment. Integration issues in health organizations have been a major obstacle to the widespread adoption of AI in healthcare compared to the accuracy of the suggestions. Natural language processing (NLP) is a form of artificial intelligence that allows computers to interpret and use human language.
Some EHR software providers are starting to incorporate limited AI health analysis features into their product offerings, but they are in the elementary stages. The use of Artificial Intelligence in healthcare promises a future full of advances, better health outcomes and better experiences for patients. Companies are taking advantage of big data to help healthcare organizations and researchers read trends to improve health conditions. AI is transforming the way patients receive quality care, while mitigating costs for providers and improving health outcomes.
To take full advantage of the use of artificial intelligence in healthcare through a separate EHR system, providers will need to carry out major integration projects on their own or take advantage of the capabilities of third-party providers that have AI capabilities and can integrate with their EHR.
