Prognostic impact of targetable driver alterations in resected early-stage lung cancer.

Background: Apart from fusions and the common mutations, targetable molecular alterations are irrelevant for adjuvant treatment decision making in early-stage non-small cell lung cancer (NSCLC). This retrospective analysis aimed to investigate if there is a difference in recurrence-free survival in stage I-III NSCLC harboring druggable molecular alterations compared to subtypes without targetable molecular alterations.

Methods: All consecutive patients who underwent surgery with curative intent for NSCLC (stage I-III) with targetable mutations between January 2015 and December 2020 at three Austrian institutions were identified and compared with tumors without targetable molecular alterations.

Multi-channel lung sound classification with convolutional recurrent neural networks.

In this paper, we present an approach for multi-channel lung sound classification, exploiting spectral, temporal and spatial information. In particular, we propose a frame-wise classification framework to process full breathing cycles of multi-channel lung sound recordings with a convolutional recurrent neural network. With our recently developed 16-channel lung sound recording device, we collect lung sound recordings from lung-healthy subjects and patients with idiopathic pulmonary fibrosis (IPF), within a clinical trial.

Interposition of Retrosternal Pedicled Jejunum After Hypopharyngolaryngo-Esophagogastrectomy.

Reconstruction of the upper gastrointestinal tract presents a surgical challenge after esophagogastrectomy, especially when it includes hypopharyngolaryngectomy. Reconstruction is generally undertaken with interposed colon as a substitute conduit, but it carries several risks. Alternative reconstruction of the foregut with pedicled retrosternal jejunum anastomosed at the level of the base of the tongue is described.

Crackle and Breathing Phase Detection in Lung Sounds with Deep Bidirectional Gated Recurrent Neural Networks.

In this paper, we present a method for event detection in single-channel lung sound recordings. This includes the detection of crackles and breathing phase events (inspiration/expiration). Therefore, we propose an event detection approach with spectral features and bidirectional gated recurrent neural networks (BiGRNNs).

Analysis of horse-related injuries in children.

Purpose: The purpose of the present study was to investigate factors affecting the nature, characteristics, severity and outcome of horseback and horse care injuries in paediatric patients and to create guidelines for injury prevention.

Methods: Detailed clinical records of 265 children sustained horse-riding related injuries have been analysed. Questionnaires were mailed to provide follow-up information for patients who have been treated in either Department of Paediatric Surgery in Pécs, Hungary, or Department of Paediatric Surgery in Graz, Austria between 1999 and 2003.