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In this thesis, we focus on predicting diagnosis from drug treatment.We investigate if such a
task can benefit from recent advances in Natural Language Processing (NLP), transfer learning techniques, and in particular the new state-of-the-art transformer-based BERT models.
The paper shows a comparison of traditional machine learning methods, deep learning methods and pre-trained BERT models for predicting diagnosis. During the evaluation step, we
found simple traditional models and deep learning models to be more effective on the task
in question. The paper further discussed why pre-trained BERT models failed to deliver
results.
This guidebook and its research results stem from the interregional collaboration of the STOB regions project.
The project, funded by the EU Commission, Interreg Europe, deals with the specific characteristics and challenges of business succession in small and medium enterprises (SME) in the European Union and addresses the complexity of the entire transfer process.
From the first thoughts of an owner to sell the business to the actual
transfer and beyond. Fundamentally, the project addresses all types of successions and transfers of business: family-internal transfers to, e.g., children and external transfers to investors or employees.
It also includes shared solutions where only (a part of the) management is handled externally, and ownership is not (or just partly) transferred.
Eine Koalitionsarbeitsgruppe erstellte einen Entwurf für ein Agrarstrukturgesetz (ASG LSA) und legte ihn im November 2020 als Drucksache 7/6804 dem Landtag vor. Dieser Beitrag unterzieht den Entwurf einer ersten rechtswissenschaftlichen Würdigung und soll damit dem Gesetzgeber für das weitere parlamentarische Verfahren Hinweise und Anregungen geben.