Automatic structuring and correction suggestion system for Hungarian clinical records

The first steps of processing clinical documents are structuring and normalization. In this paper we demonstrate how we compensate the lack of any structure in the raw data by transforming simple formatting features automatically to structural units. Then we developed an algorithm to separate running text from tabular and numerical data. Finally we generated correcting suggestions for word forms recognized to be incorrect. Some evaluation results are also provided for using the system as automatically correcting input texts by choosing the best possible suggestion from the generated list. Our method is based on the statistical characteristics of our Hungarian clinical data set and on the HUMor Hungarian morphological analyzer. The conclusions claim that our algorithm is not able to correct all mistakes by itself, but is a very powerful tool to help manually correcting Hungarian medical texts in order to produce a correct text corpus of such a domain

A scoping review of natural language processing of radiology reports in breast cancer

Various natural language processing (NLP) algorithms have been applied in the literature to analyze radiology reports pertaining to the diagnosis and subsequent care of cancer patients. Applications of this technology include cohort selection for clinical trials, population of large-scale data registries, and quality improvement in radiology workflows including mammography screening. This scoping review is the first to examine such applications in the specific context of breast cancer. Out of 210 identified articles initially, 44 met our inclusion criteria for this review. Extracted data elements included both clinical and technical details of studies that developed or evaluated NLP algorithms applied to free-text radiology reports of breast cancer. Our review illustrates an emphasis on applications in diagnostic and screening processes over treatment or therapeutic applications and describes growth in deep learning and transfer learning approaches in recent years, although rule-based approaches continue to be useful. Furthermore, we observe increased efforts in code and software sharing but not with data sharing

Helyesírási hibák automatikus javítása orvosi szövegekben a szövegkörnyezet figyelembevételével

Cikkünkben egy korábban bemutatott orvosi helyesírás-javító rendszer lényegesen továbbfejlesztett változatát mutatjuk be, amely a korábbival ellentétben képes az egybeírások javítására, és a szövegkörnyezetet is figyelembe veszi ennek során, így alkalmas teljesen automatikus javításra is

Proceedings of the 2nd IUI Workshop on Interacting with Smart Objects

These are the Proceedings of the 2nd IUI Workshop on Interacting with Smart Objects. Objects that we use in our everyday life are expanding their restricted interaction capabilities and provide functionalities that go far beyond their original functionality. They feature computing capabilities and are thus able to capture information, process and store it and interact with their environments, turning them into smart objects

Elírások automatikus detektálása és javítása radiológiai leletek szövegében

A radiológiai leletezés közben gyakran előfordulhatnak szövegbéli hibák, melyek kézi javításra szorulnak. Ez időt von el a radiológustól, valamint a hibák sikertelen felismerése nyomán rontja a leletek minőségét és utólagos gépi feldolgozhatóságát is. Cikkünkben magyar nyelvű gerincleletek elírásainak automatikus kijavításával foglalkozunk. Ismertetjük az általunk felhasznált módszereket, és megmutatjuk, hogy az elírások automatikus javítása az értelmezést is nagymértékben javítja. Módszerünket 882 valós lelet kézi hibajavításával vetjük össze