NLP (Natural Language Processing) – one of the artificial intelligence technologies that enables computers to learn, interpret, and generate human language. NLP surrounds us everywhere – the technology is used in search engines, as well as for the stable operation of virtual assistants, including chatbots.
Tasks that NLP solves:
- Text classification. The technology automatically distributes documents by topic, for example, commercial offers, holiday greetings, complaints, contracts, etc.
- Sentiment analysis. Determining the emotional tone of the text.
- Named entity recognition. Identifying proper names, company names, cities, and other important objects in the text.
- Machine translation. Translating text from one language to another.
- Question-answering. Finding the answer to a question in the text or knowledge base.
- Text summarization. Creating a summary of a long text.
- Text generation. Automatically creating texts of various genres: articles, abstracts, interviews, posts, etc.
- Speech recognition and synthesis. Converting spoken language into text and vice versa.
- Dependency analysis. Determining the grammatical relationships between words in a sentence. Helps the computer understand the structure of the sentence and the relationships between words.
- Relationship extraction. Identifying relationships between entities in the text.
In which areas is NLP actively used?
- Marketing and business. NLP technology analyzes a product and determines whether it pays off well and generates profit.
- Investment activity. The system helps to make a decision on the feasibility of acquiring shares of a particular company.
- Jurisprudence. Natural language processing methods are used to analyze laws and other legal documents.
- Robotics. NLP allows robots to correctly recognize human speech and read its emotional tone.
- Education. Teachers use NLP to detect plagiarism and grammatical errors in student work.
How Ingosstrakh implements NLP in medicine
With the development of artificial intelligence, we are seeing an expansion of the possibilities of using NLP. Currently, one of the most promising areas is the use of this technology in medicine.
The key advantage of natural language processing is the ability to process large amounts of unstructured data, such as documents, medical records, and tests in the shortest possible time. For example, NLP systems are able to analyze patient records and identify patterns that can help in the diagnosis and treatment of diseases. This is especially important in situations where time is of the essence.
NLP can be used as a prompt for doctors, for example, to show contraindications to prescribed drugs or to suggest taking tests based on the patient's medical history. NLP helps in radiology, where programs predict diagnoses based on the description of X-rays and automatically assign international disease codes to them.
This technology is already being used in chatbots for interacting with patients, and major global medical centers are implementing it in their practice. For example, the Amazon Comprehend Medical service extracts data on diseases and treatments from medical documentation, which allows predicting the development of various health conditions, such as cardiovascular diseases and depression.
Ingosstrakh is also developing in the direction of artificial intelligence in medicine. One of the most important projects now is the implementation of AI to determine the patient's diagnosis based on their complaints. This technology based on NLP serves as an assistant to doctors, helps to make a preliminary diagnosis, after which, based on the analysis of all data and the patient's medical record, the doctor makes a diagnosis. The specialist enters patient complaints into the service, which are analyzed, and at the output we get the top 3 most likely diagnoses of this patient. Based on the data obtained and their professional experience, the doctor draws conclusions and makes a medical report.
NLP also helps doctors in routine work. Specialists can fill out patient cards by voice – the human language processing technology transcribes the doctor's voice and independently fills out the medical card, which allows more time and attention to be given to patients. In addition, NLP records telephone conversations between patients and operators, based on which it also enters data into their cards.
The key value of the tool is that the service helps doctors in those areas where the doctor first communicates with the patient, and then restores information from memory or their records, spending time on it. The tool helps endoscopists: the doctor speaks the results of the procedure aloud, and the system recognizes the speech and automatically issues a protocol. Currently, a solution is being developed for procedures such as gastroscopy, colonoscopy, rectoscopy, rhinoscopy, and otoscopy.
In the foreseeable future, we will witness the widespread introduction of artificial intelligence in medicine. However, it is important to remember that any technology or innovation is only an assistant in the hands of medical professionals. Artificial intelligence cannot replace human experience, intuition, and empathy, which remain key aspects in the treatment of patients.
Ksenia Ivashkevich,
Director of Digital Innovation in Medicine at Ingosstrakh