The use of Artificial intelligence in the healthcare space is on the up and up. Some of the most compelling AI applications leverage natural language processing(NLP). The world has already seen advances in the education space, from grammar suggestions to creating powerful learning experiences. NLP has this unique ability to understand unstructured data which makes it a great choice for applications in the healthcare space. The global market for NLP in healthcare and Life Sciences is growing at a CAGR of 19% and is expected to reach $4.3 billion by 2026. As data literacy improves amongst patients and corporations alike, generating valuable insights from EHR and other health records data might end up being the driving factor for growth in this space. Given that data-driven technologies are more accessible than ever, it is expected to improve healthcare outcomes while driving growth in business opportunities. NLP could potentially be the key to effective patient care but there are many problems to solve before an industry-wide adoption. Here’s the perfect guide to understanding the potential impact on NLP on the healthcare industry.
Natural language processing(NLP) is the branch of AI that involves getting machines to understand the natural language. It is often said to be an intersection of computer science, linguistics and machine learning. The world generates a staggering 2.5 quintillion bytes of data every single day with upto eighty to ninety percent of the data in question being unstructured. NLP has the ability to convert all of that unstructured data into structured data which provides us the opportunity to gain insights from it. NLP has a wide array of applications ranging from voice assistants like Alexa and Siri, sentiment analysis tools like Text Analytics to text generation tools like GPT-3. NLP applications can be broadly classified into three categories:
NLP has the potential of revolutionizing the entire healthcare system. From better patient care to assistance in decision-making for doctors to advancements in medical research, NLP has a host of fairly obvious benefits. Some of them are:
Natural Language Processing has seen a recent increase in applications in the healthcare sector. One of the most important of these is in medical imaging. Although MRI scans are fast and more accurate than traditional x-rays, they come with a host of caveats that can be difficult for patients to understand, such as their likelihood of developing cancer, the probability of the cancer returning, or the chance that they might have an infection. Natural Language Processing is being used to interpret MRI scan reports. Here are some of the most common practical applications of NLP in healthcare:
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