Awakening from Sleep with Numbness and Indescribable Odd Feeling: Nocturnal Panic Attack or Sleep-Related Epilepsy?

Paroxysmal events during sleep can be classified into parasomnias, sleep-related movements, psychiatric events, neurologic events, or medically related events. Diagnosis can be difficult because of the frequent overlap of clinical descriptors and lack of diurnal findings. We report a case of a 68-year-old man who presented to the hospital complaining of awakening from sleep with numbness, which was followed by an indescribable odd feeling. We discuss overlapping clinical features of nocturnal panic and sleep-related epilepsy

Awakening from Sleep with Numbness and Indescribable Odd Feeling: Nocturnal Panic Attack or Sleep-Related Epilepsy?

Paroxysmal events during sleep can be classified into parasomnias, sleep-related movements, psychiatric events, neurologic events, or medically related events. Diagnosis can be difficult because of the frequent overlap of clinical descriptors and lack of diurnal findings. We report a case of a 68-year-old man who presented to the hospital complaining of awakening from sleep with numbness, which was followed by an indescribable odd feeling. We discuss overlapping clinical features of nocturnal panic and sleep-related epilepsy

Staatliche Finanzierung für innovative Exportunternehmen

Innovationen sind wichtige Treiber für ökonomisches Wachstum und sind für erfolgreiche Volkswirtschaften von zentraler Bedeutung. In Ländern wie Deutschland, Finnland oder Großbritannien sorgen ein innovationsfreundliches gesellschaftliches Klima, die Entwicklung von Spitzentechnologien an Universitäten und Hochschulen sowie privatwirtschaftliche Innovationstätigkeit für langfristigen Wohlstand. Neben multinationalen Konzernen sind kleine und mittlere Unternehmen (KMU) häufig Treiber von innovativen Ideen

Why is the winner the best?

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and successful participation strategies? What makes a solution superior to a competing method? To address this gap in the literature, we performed a multi-center study with all 80 competitions that were conducted in the scope of IEEE ISBI 2021 and MICCAI 2021. Statistical analyses performed based on comprehensive descriptions of the submitted algorithms linked to their rank as well as the underlying participation strategies revealed common characteristics of winning solutions. These typically include the use of multi-task learning (63%) and/or multi-stage pipelines (61%), and a focus on augmentation (100%), image preprocessing (97%), data curation (79%), and postprocessing (66%). The "typical" lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning. Two core general development strategies stood out for highly-ranked teams: the reflection of the metrics in the method design and the focus on analyzing and handling failure cases. According to the organizers, 43% of the winning algorithms exceeded the state of the art but only 11% completely solved the respective domain problem. The insights of our study could help researchers (1) improve algorithm development strategies when approaching new problems, and (2) focus on open research questions revealed by this work