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1. WO2020115487 - METHOD AND DATA PROCESSING APPARATUS FOR GENERATING REAL-TIME ALERTS ABOUT A PATIENT

Publication Number WO/2020/115487
Publication Date 11.06.2020
International Application No. PCT/GB2019/053437
International Filing Date 05.12.2019
IPC
G16H 50/20 2018.01
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
50ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
20for computer-aided diagnosis, e.g. based on medical expert systems
G16H 50/70 2018.01
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
50ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
70for mining of medical data, e.g. analysing previous cases of other patients
G06N 3/04 2006.01
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architecture, e.g. interconnection topology
CPC
G06N 3/0445
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architectures, e.g. interconnection topology
0445Feedback networks, e.g. hopfield nets, associative networks
G06N 3/0454
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architectures, e.g. interconnection topology
0454using a combination of multiple neural nets
G06N 3/0472
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architectures, e.g. interconnection topology
0472using probabilistic elements, e.g. p-rams, stochastic processors
G06N 7/005
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
7Computer systems based on specific mathematical models
005Probabilistic networks
G16H 50/20
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
50ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
20for computer-aided diagnosis, e.g. based on medical expert systems
G16H 50/70
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
50ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
70for mining of medical data, e.g. analysing previous cases of other patients
Applicants
  • OXFORD UNIVERSITY INNOVATION LIMITED [GB]/[GB]
Inventors
  • ZHU, Tingting
  • SHAMOUT, Farah
  • CLIFTON, David
  • WATKINSON, Peter
Agents
  • J A KEMP LLP
Priority Data
1820004.807.12.2018GB
Publication Language English (EN)
Filing Language English (EN)
Designated States
Title
(EN) METHOD AND DATA PROCESSING APPARATUS FOR GENERATING REAL-TIME ALERTS ABOUT A PATIENT
(FR) PROCÉDÉ ET APPAREIL DE TRAITEMENT DE DONNÉES POUR GÉNÉRER DES ALERTES EN TEMPS RÉEL CONCERNANT UN PATIENT
Abstract
(EN)
This disclosure relates to methods and apparatus for generating real-time alerts about a patient. In one arrangement, vital sign data representing vital sign information obtained from the patient at one or more input times within an assessment time window is received. A Gaussian process model of at least a portion of the vital sign information is used to generate a time series of synthetic vital sign data based on the received vital sign data, the synthetic vital sign data comprising at least a posterior mean for each of one or more components of the vital sign information at each of a plurality of regularly spaced time points in the assessment time window. The generated synthetic vital sign data is used as input to a trained recurrent neural network to generate an early warning score, the early warning score representing a probability of an adverse event occurring during a prediction time window of predetermined length after the assessment time window. An alert is generating about the patient dependent on the generated early warning score.
(FR)
L'invention se réfère à des procédés et à un appareil pour générer des alertes en temps réel concernant un patient. Dans un agencement, des données de signes vitaux représentant des informations de signes vitaux provenant du patient, à un ou plusieurs instant(s) d'entrée dans une fenêtre de temps d'évaluation, sont reçues. Un modèle de processus gaussien d'au moins une partie des informations de signes vitaux est utilisé pour générer une série chronologique de données synthétiques de signes vitaux sur la base des données de signes vitaux reçues, les données synthétiques de signes vitaux comprenant au moins une moyenne corrigée pour chaque composante parmi une ou plusieurs composante(s) des informations de signes vitaux, à chacun d'une pluralité de points temporels régulièrement espacés dans la fenêtre de temps d'évaluation. Les données synthétiques de signes vitaux générées sont appliquées à l'entrée d'un réseau neuronal récurrent entraîné pour générer un score d'avertissement précoce, le score d'avertissement précoce représentant la probabilité de survenue d'un événement indésirable pendant une fenêtre de temps de prédiction de longueur prédéfinie après la fenêtre de temps d'évaluation. Une alerte est générée concernant le patient en fonction du score d'avertissement précoce généré.
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