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Hugo Silva, Vítor Duque, Mário Macedo and Mateus Mendes
The International Classification of Diseases, 10th edition (ICD-10), has been widely used for the classification of patient diagnostic information. This classification is usually performed by dedicated physicians with specific coding training, and it is ...
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Salvatore Calcagno, Andrea Calvagna, Emiliano Tramontana and Gabriella Verga
The Electronic Health Record (EHR) is a system for collecting and storing patient medical records as data that can be mechanically accessed, hence facilitating and assisting the medical decision-making process. EHRs exist in several formats, and each for...
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Matthias Kleinert, Oliver Ohneiser, Hartmut Helmke, Shruthi Shetty, Heiko Ehr, Mathias Maier, Susanne Schacht and Hanno Wiese
The information air traffic controllers (ATCos) communicate via radio telephony is valuable for digital assistants to provide additional safety. Yet, ATCos have to enter this information manually. Assistant-based speech recognition (ABSR) has proven to b...
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Oliver Ohneiser, Hartmut Helmke, Shruthi Shetty, Matthias Kleinert, Heiko Ehr, Sebastian Schier-Morgenthal, Saeed Sarfjoo, Petr Motlicek, ?arunas Murauskas, Tomas Pagirys, Haris Usanovic, Mirta Me?trovic and Aneta Cerná
Assistant Based Speech Recognition (ABSR) systems for air traffic control radiotelephony communication have shown their potential to reduce air traffic controllers? (ATCos) workload. Related research activities mainly focused on utterances for approach a...
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Nils Ahrenhold, Hartmut Helmke, Thorsten Mühlhausen, Oliver Ohneiser, Matthias Kleinert, Heiko Ehr, Lucas Klamert and Juan Zuluaga-Gómez
Automatic speech recognition and understanding (ASRU) for air traffic control (ATC) has been investigated in different ATC environments and applications. The objective of this study was to quantify the effect of ASRU support for air traffic controllers (...
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Massimiliano Greco, Pier Francesco Caruso, Sofia Spano, Gianluigi Citterio, Antonio Desai, Alberto Molteni, Romina Aceto, Elena Costantini, Antonio Voza and Maurizio Cecconi
Background: Sepsis is one of the major causes of in-hospital death, and is frequent in patients presenting to the emergency department (ED). Early identification of high-risk septic patients is critical. Machine learning (ML) techniques have been propose...
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Raza Nowrozy, Khandakar Ahmed, Hua Wang and Timothy Mcintosh
This paper proposed a novel privacy model for Electronic Health Records (EHR) systems utilizing a conceptual privacy ontology and Machine Learning (ML) methodologies. It underscores the challenges currently faced by EHR systems such as balancing privacy ...
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Marco-Michael Temme, Olga Gluchshenko, Lennard Nöhren, Matthias Kleinert, Oliver Ohneiser, Kathleen Muth, Heiko Ehr, Niklas Groß, Annette Temme, Martina Lagasio, Massimo Milelli, Vincenzo Mazzarella, Antonio Parodi, Eugenio Realini, Stefano Federico, Rosa Claudia Torcasio, Markus Kerschbaum, Laura Esbrí, Maria Carmen Llasat, Tomeu Rigo and Riccardo Biondiadd Show full author list remove Hide full author list
In the H2020 project ?Satellite-borne and INsitu Observations to Predict The Initiation of Convection for ATM? (SINOPTICA), an air traffic controller support system was extended to organize approaching traffic even under severe weather conditions. During...
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Hassan El-khatib, Ana-Maria ?tefan and Dan Popescu
The incidence of melanoma cases continues to rise, underscoring the critical need for early detection and treatment. Recent studies highlight the significance of deep learning in melanoma detection, leading to improved accuracy. The field of computer-ass...
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Yijun Shao, Kaitlin Todd, Andrew Shutes-David, Steven P. Millard, Karl Brown, Amy Thomas, Kathryn Chen, Katherine Wilson, Qing T. Zeng and Debby W. Tsuang
The application of natural language processing and machine learning (ML) in electronic health records (EHRs) may help reduce dementia underdiagnosis, but models that are not designed to reflect minority populations may instead perpetuate underdiagnosis. ...
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