The open set of tasks in healthcare domain
Successful development and application of deep learning methods to new fields of knowledge are impossible without using specialized benchmarks and data.
The shortage of such resources is particularly pervasive in highly regulated subject areas. A prime example is the field of automatic natural language processing (NLP) in medicine. This problem, in particular, is also relevant for the Russian language, as the open medical data sets and machine learning problem definitions are extremely limited.
We offer an open benchmark that allows testing ML-models in a wide range of medical tasks.