Medica l Image Ana lysis & Ar t i f icia l Intel l igence Symposium 2022 Curriculum Vitae: Dr. Ross King completed his BS degree in Engineering Physics from the Colorado School of Mines in 1988. He went on to write his Ph.D degree in Physics at Stanford University. Following positions at Institute for Medium Energy Physics (IMEP) where he headed the Electronics Department, as well as Alpha Thinx Mobile Phone Services AG and uma information technology AG where he held positions as senior manager and technical director respectively, he went on to build up the Research Studio Digital Memory Engineering at Austrian Research Centers. Here he served on the Board of Directors of the EU FP-6 Integrated Projects BRICKS as well as on the Scientific Board of the EU FP-6 Integrated Project Planets. Starting at Austrian Institute of Technology GmbH (AIT) in 2008 he played an integral part in the Digital Safety and Security Information Management. Here he coordinated the FFG Research Studios Project “Digital Memory Engineering” and went on to become AIT Thematic Coordinator for Data Science and subsequently Head of the DSAI Competence Unit. Dr. Ross King is member of the Big Data Value Association (BDVA) and served as Chairman of the Board of the Open Preservation Foundation from 2013 until 2017. He is the author of numerous Computer Science Publications. Abstract: Audio Analysis for Medical Diagnostics Dr. King will present a paper describing a neural network model for the multiclass classification of coughs based on the Respiratory Sound database that was originally compiled to support the scientific challenge organized at Int. Conf. on Biomedical Health Informatics - ICBHI 2017. The paper approaches the challenge of audio analysis by converting the audio signal to an image signal using spectrogram analysis, then appliying convolutional neural networks to the results image. The resulting model combines inception networks with ensemble learning and compares well with other state-of-the art published models. At the same time, Dr. King will use this paper as an example of how machine learning is applied in general, what some of the challenges are, and what improvements are necessary in order to advance the use machine learning as a tool for medical diagnostics. Dr. Ross King Head of Competence Unit Data Science & Artificial Intelligence AIT Austrian Institute of Technology GmbH
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