[Potential applications of deep learning-based technologies in Hungarian mammography]. / A számítógépes mélytanulási technológia várható megjelenése a hazai mammográfiában.

INTRODUCTION AND AIM: The technology, named 'deep learning' is the promising result of the last two decades of development in computer science. It poses an unavoidable challenge for medicine, how to understand, apply and adopt the - today not fully explored - possibilities that have become available by these new methods. METHOD: It is a gift and a mission, since the exponentially growing volume of raw data (from imaging, laboratory, therapy diagnostics or therapy interactions, etc.) did not solve until now our wished and aimed goal to treat patients according to their personal status and setting or specific to their tumor and disease. RESULTS: Currently, as a responsible health care provider and financier, we face the problem of supporting suboptimal procedures and protocols either at individual or at community level. The problem roots in the overwhelming amount of data and, at the same time, the lack of targeted information for treatment. We expect from the deep learning technology an aid which helps to reinforce and extend the human-human cooperations in patient-doctor visits. We expect that computers take over the tedious work allowing to revive the core of healing medicine: the insightful meeting and discussion between patients and medical experts. CONCLUSION: We should learn the revelational possibilities of deep learning techniques that can help to overcome our recognized finite capacities in data processing and integration. If we, doctors and health care providers or decision makers, are able to abandon our fears and prejudices, then we can utilize this new tool not only in imaging diagnostics but also for daily therapies (e.g., immune therapy). The paper aims to make a great mind to do this. Orv Hetil. 2019; 160(4): 138-143.

Minor physical anomalies are more common in children with idiopathic epilepsy.

BACKGROUND: The prevalence of minor physical anomalies (prenatal errors of morphogenesis) was evaluated in patients with idiopathic epilepsy to get indirect data on the possible role of aberrant neurodevelopment in the etiology of the disease. AIM: Connecting to current opinions on a possible role of aberrant neurodevelopment in idiopathic epilepsy it seems important to introduce somatic trait marker research focusing on brain maldevelopment. METHODS: A scale developed by Méhes (1985) was used to detect the presence or absence of 57 minor physical anomalies in 24 patients with idiopathic epilepsy and in 24 matched controls. RESULTS: The mean value of all minor physical anomalies was significantly higher in the group of patients compared to controls. In case of 3 minor physical anomalies we could demonstrate statistically significant differences between children with epilepsy and the control sample. Two minor malformations (primitive shape of ears, double posterior hair whorl) and one phenogenetic variant (inner epicanthic folds) had a significantly higher frequency in patients compared to control individuals. CONCLUSION: The overrepresentation of minor physical anomalies in idiopathic epilepsy can strongly support the view that this disorder is related to pathological factors operating early in development.