Cinque Terre

Medical field is an endless source of information.

Artificial Intelligence (AI) technologies are actively developing in at least two main areas - image processing and natural language processing. Both directions are of great interest to medicine, but still, work with images today has taken a leading position.

AI-based solutions are already actively used by doctors radiology, dermatology, pathology, ophthalmology, etc. In radiology, for example, human capabilities are surpassed, but ethical issues do not yet allow a complete replacement of a specialist. Obviously, it will still happen when the time is right.

You can also recall such areas as sound processing, some electrical signals, such as ECG and much more, but we will focus on natural language Processing (NLP). More specifically, NLP and Deep Learning (DL) in the medical field.

Communication between a doctor and a patient almost always involves a conversation. Speech is a source of live, up-to-date information about the patients problems. Speech is not just a description of complaints or symptoms. It is also emotions, context. Correctly asked questions in a conversation significantly increase the information load of an ordinary story.

Unfortunately, today there are very few NLP-solutions, that would be useful in healthcare. In addition, to routine neural networks for determining the tone of the text, you will not find anything. Neural Networks have received maximum development for use in the English language. For other languages, they are much less. For example, in the Ukrainian segment of research on this topic, you will find practically nothing today.

On the other hand, in the medical field, a huge amount of new data is constantly being generated. The volume of information is progressively increasing, and it is an interesting material for new exciting discoveries in the field of AI.

Obviously, it is for these reasons that the field of machine learning for natural language processing has become a research priority for me.


This site provides examples of the possible use of solutions, based on NN, ML and NLP technologies. Ask questions, let us your suggestions here .

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