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NLP is making remarkable advancements in the medical field to a level that has only been addressed in sci-fi films. This branch of artificial intelligence aims to make computers conversant with text and speech and translate text to speech in a comprehensive way. Given the growing use of technology to enhance patient-centric outcomes, the advancements in NLP are all set to play an active role.
One of the biggest advantages of NLP in healthcare management is the opportunity to analyze a huge amount of unstructured data. A report released by the International Data Corporation has estimated that at least 80% of the healthcare data is unstructured and emanates from physicians' documentation, tests, and discharge summaries. This mass of information can be pre-searched using NLP tools to identify the content and data that may be important to clinical determination in a short period. For example, NLP algorithms can distinguish vital details of the patient, which can help care for the patient while reducing the time spent on documentation.
NLP is also improving the patient experience. Envision a situation where patients could ask chatbots for medical advice when they encounter problems. Utilizing artificial intelligence, these systems can give details on the symptoms, the drugs, and even an appointment. Chatbots in the healthcare industry will likely reduce healthcare costs to $3 billion per annum by 2022, as revealed by a study by Juniper Research. While benefiting patients, this innovation is also helpful in decreasing pressure on the staff of healthcare centres.
Another application of NLP is predictive analysis, which is also enjoying steady advancement. NLP can determine patients' possible health outcomes and conditions using patient history and published materials. According to research conducted in Health Affairs, deploying NLP to explore EHR enhanced the detection of high-risk patients by 50%. With predictive capacity for the development of diseases, it becomes easier for healthcare providers to intervene early enough and possibly save lives and quite a lot of money.
NLP is very helpful in medical research. It helps researchers find important information quickly by scanning large databases of reports and studies, speeding up the discovery of new treatments. For example, researchers at Stanford University used NLP to study thousands of research papers quickly, helping them discover new ways to treat diseases like cancer faster than humans could.
But there are still some problems. One big challenge is making sure NLP systems are always correct. If they misunderstand medical words or patient details, it could cause serious mistakes. However, as these technologies improve, efforts are being made to make them more accurate and easier to use in hospitals.
In short, NLP is changing the medical field in many ways. It improves how doctors talk with patients and speed up research. By better understanding data and predicting health outcomes, NLP is becoming a valuable tool for doctors. With these new technologies, the future of healthcare looks brighter, with better treatments and faster processes ahead.
