9 research outputs found
Transforming unstructured voice and text data into insight for paramedic emergency service using recurrent and convolutional neural networks
Paramedics often have to make lifesaving decisions within a limited time in
an ambulance. They sometimes ask the doctor for additional medical
instructions, during which valuable time passes for the patient. This study
aims to automatically fuse voice and text data to provide tailored situational
awareness information to paramedics. To train and test speech recognition
models, we built a bidirectional deep recurrent neural network (long short-term
memory (LSTM)). Then we used convolutional neural networks on top of
custom-trained word vectors for sentence-level classification tasks. Each
sentence is automatically categorized into four classes, including patient
status, medical history, treatment plan, and medication reminder. Subsequently,
incident reports were automatically generated to extract keywords and assist
paramedics and physicians in making decisions. The proposed system found that
it could provide timely medication notifications based on unstructured voice
and text data, which was not possible in paramedic emergencies at present. In
addition, the automatic incident report generation provided by the proposed
system improves the routine but error-prone tasks of paramedics and doctors,
helping them focus on patient care
32. Forum Bauinformatik 2021
Das Forum Bauinformatik ist eine jährlich stattfindende Tagung und ein wichtiger Bestandteil der Bauinformatik im deutschsprachigen Raum. Insbesondere Nachwuchswissenschaftlerinnen und -wissenschaftlern bietet es die Möglichkeit, ihre Forschungsarbeiten zu präsentieren, Problemstellungen fachspezifisch zu diskutieren und sich über den neuesten Stand der Forschung zu informieren. Es bietet sich ausgezeichnete Gelegenheit, in die wissenschaftliche Gemeinschaft im Bereich der Bauinformatik einzusteigen und Kontakte mit anderen Forschenden zu knüpfen
Psychological Engagement in Choice and Judgment Under Risk and Uncertainty
Theories of choice and judgment assume that agents behave rationally, choose the higher expected value option, and evaluate the choice consistently (Expected Utility Theory, Von Neumann, & Morgenstern, 1947). However, researchers in decision-making showed that human behaviour is different in choice and judgement tasks (Slovic & Lichtenstein, 1968; 1971; 1973). In this research, we propose that psychological engagement and control deprivation predict behavioural inconsistencies and utilitarian performance with judgment and choice. Moreover, we explore the influences of engagement and control deprivation on agent’s behaviours, while manipulating content of utility (Kusev et al., 2011, Hertwig & Gigerenzer 1999, Tversky & Khaneman, 1996) and
decision reward (Kusev et al, 2013, Shafir et al., 2002)