Natural language processing (NLP) is an area of artificial intelligence that enables computers to recognize and comprehend human speech. NLP refers to software-based technologies that facilitate the translation of the natural language used by humans in speech and writing (Manning et al ., 2014). Academics at Stanford University developed NLP. Before initiating the data processing pipeline, NLP systems purify the dataset ( Azeroual , 2020). This involves arranging the material logically, for instance, by tokenizing the language into smaller semantic pieces. Through pre-processing, the NLP system's comprehension of the dataset is facilitated. To decipher the text, the system incorporates a variety of text-interpretation-related algorithms. The two basic natural language processing algorithms are rule-based systems and machine learning models (Kang et al ., 2013). Rule-based approaches translate text based on predefined grammatical rules, whereas machine learning models employ statistical methodology and learn over time by being fed training data (Kang et al ., 2013).

NLP uses speech-to-text dictation and structured data entry at the point of treatment to extract critical data from EHR rather than spending a substantial amount of time manually evaluating complex EHR. This saves a substantial amount of time. This allows medical practitioners to focus on delivering the necessary treatment for their patients and ensures that clinical documentation is accurate and up-to-date.