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Akademický článek

Bus journey simulation to develop public transport predictive algorithms

Autor: Thilo Reich, Marcin Budka, David Hulbert

Publikováno v: Soft Computing Letters, Vol 3, Iss , Pp 100029- (2021)

Encouraging the use of public transport is essential to combat congestion and pollution in an urban environment. To achieve this, the reliability of arrival time prediction should be improved as this is one area of improvement frequently requested by

Externí odkaz: https://doaj.org/article/f5158e14a3764859b0222214c266607f

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Akademický článek

A Model Architecture for Public Transport Networks Using a Combination of a Recurrent Neural Network Encoder Library and a Attention Mechanism

Autor: Thilo Reich, David Hulbert, Marcin Budka

Publikováno v: Algorithms, Vol 15, Iss 9, p 328 (2022)

This study presents a working concept of a model architecture allowing to leverage the state of an entire transport network to make estimated arrival time (ETA) and next-step location predictions. To this end, a combination of an attention mechanism

Externí odkaz: https://doaj.org/article/bfe49e8c08e349cc92342fa4f6e20749

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Towards an automated app-based dose prescription of carbimazole for hyperthyroidism patients

Autor: Thilo Reich, Rashid Bakirov, Dominika Budka, Derek Kelly, James Smith, Tristan Richardson, Marcin Budka

Publikováno v: Endocrine Abstracts.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2abdfa2311f87e73b79b249d95cb9dbb
https://doi.org/10.1530/endoabs.86.oc6.4

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An Attention Mechanism Based Prediction Method for Estimation of Arrival Time and Next-Step Position in Urban Traffic Networks

Autor: Thilo Reich, Marcin Budka, David Hulbert

Publikováno v: SSRN Electronic Journal.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c2843281ba1d22b068b4dfb4699c303c
https://doi.org/10.2139/ssrn.4148559

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Proof of concept for a syndromic surveillance system based on routine ambulance records in the South West of England, for the influenza season 2016/2017

Autor: Marcin Budka, Thilo Reich

Publikováno v: Br Paramed J

INTRODUCTION: The introduction of electronic patient records in the ambulance service provides new opportunities to monitor the population. Approximately 36% of patients presenting to English ambulance services are discharged at scene. Ambulance reco

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f46ea601c6ee3350766b39e7cbae920a
https://doi.org/10.29045/14784726.2019.09.4.2.22

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Impact of Data Quality and Target Representation on Predictions for Urban Bus Networks

Autor: Marcin Budka, Thilo Reich, David Hulbert

Publikováno v: SSCI

Passengers of urban bus networks often rely on forecasts of Estimated Times of Arrival (ETA) and live-vehicle movements to plan their journeys. ETA predictions are unreliable due to the lack of good quality historical data, while ‘live’ positions

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ca89eb7a27a04a88e052cd0ef0e8c48a
https://doi.org/10.1109/ssci47803.2020.9308166

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EP11 Using machine learning to recover unrecorded prehospital data

Autor: Adam Bancroft, Marcin Budka, Thilo Reich

Publikováno v: Emergency Medicine Journal. 38:A5.3-A6

BackgroundThe recording practices, of electronic patient records for ambulance crews, are continuously developing. South Central Ambulance Service (SCAS) adapted the common AVPU-scale (Alert, Voice, Pain, Unresponsive) in 2019 to include an option fo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bfebf492a9f27147b32c00e6cd656586
https://doi.org/10.1136/emermed-2021-999.11

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A Proof Of Concept For A Syndromic Surveillance System Based On Routine Ambulance Records In The South-west Of England, For The Influenza Season 2016/17

Autor: Marcin Budka, Thilo Reich

The introduction of electronic patient records in the ambulance service provides new opportunities to monitor the population. Most patients presenting to British ambulance services are discharged at scene. Ambulance records are therefore an ideal dat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::135ce7c98dfa9c863344626fd0b38cbe

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PP15 Predicting variations of calls to an ambulance service in the UK caused by circulating infections using-deep learning methods

Autor: Thilo Reich, Marcin Budka

Publikováno v: Emergency Medicine Journal. 36:e7.2-e7

BackgroundDigital patient records in the ambulance service have opened up new opportunities for prehospital care. Previously it was demonstrated that prehospital pyrexia numbers are linked to an increase in overall calls to the ambulance service. Thi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c67f038ae665ff5fe91abf573368062a
https://doi.org/10.1136/emermed-2019-999abs.15

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04 Using electronic patient records collected by ambulance personnel to detect disease outbreaks

Autor: Thilo Reich

Publikováno v: Emergency Medicine Journal. 36:e2.2-e2

BackgroundThe introduction of electronic patient records in the ambulance service allows to use these to monitor the population. Most patients are discharged at scene therefore this data represents a new source for syndromic disease surveillance. The

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f9d000baa613dac28cf71d0f60243cc4
https://doi.org/10.1136/emermed-2019-999.4

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