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1.
公开(公告)号:EP4334699A1
公开(公告)日:2024-03-13
申请号:EP22732636.0
申请日:2022-05-09
申请人: INESC TEC - Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência , Universidade Do Porto , ILOF - Intelligent LAB on Fiber Unipessoal Lda
发明人: DA SILVA JORGE, Pedro Alberto , BOSSI, Alessandra Maria , CENNAMO, Nunzio , SANTOS PAIVA, Joana Isabel , DA COSTA SANTOS, Paulo Henrique , MARTINS RODRIGUES, Sandra Cristina , DA SILVA CARPINTEIRO, Cristiana Raquel
IPC分类号: G01N15/06
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2.
公开(公告)号:EP4296646A2
公开(公告)日:2023-12-27
申请号:EP23207812.1
申请日:2019-10-31
发明人: DOS SANTOS PAIVA, Joana Isabel , TRIGUEIROS DA SILVA CUNHA, João Paulo , DA SILVA JORGE, Pedro Alberto
IPC分类号: G01N15/10
摘要: Device and method for detecting dispersed extracellular vesicles in a liquid dispersion sample, said method using an electronic data processor for classifying the sample as having, or not having, extracellular vesicles present, the method comprising the use of the electronic data processor for pre-training a machine learning classifier with a plurality of extracellular vesicle liquid dispersion specimens comprising the steps of: emitting a laser modulated by a modulation frequency onto each specimen; capturing a temporal signal from laser light backscattered by each specimen for a plurality of temporal periods of a predetermined duration for each specimen; calculating specimen DCT or Wavelet transform coefficients from the captured signal for each of the temporal periods; using the calculated coefficients to pre-train the machine learning classifier; wherein the method further comprises the steps of: using a laser emitter having a focusing optical system coupled to the emitter to emit a laser modulated by a modulation frequency onto the sample; using a light receiver to capture a signal from laser light backscattered by the sample for a plurality of temporal periods of a predetermined duration; calculating sample DCT or Wavelet transform coefficients from the captured signal for each of the temporal periods; using the pre-trained machine learning classifier to classify the calculated sample coefficients as having, or not having, extracellular vesicles present.
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3.
公开(公告)号:EP4296646A3
公开(公告)日:2024-03-13
申请号:EP23207812.1
申请日:2019-10-31
发明人: DOS SANTOS PAIVA, Joana Isabel , TRIGUEIROS DA SILVA CUNHA, João Paulo , DA SILVA JORGE, Pedro Alberto
IPC分类号: G01N15/0205 , G01N15/10 , G01N15/1429 , G01N15/14
摘要: Device and method for detecting dispersed extracellular vesicles in a liquid dispersion sample, said method using an electronic data processor for classifying the sample as having, or not having, extracellular vesicles present, the method comprising the use of the electronic data processor for pre-training a machine learning classifier with a plurality of extracellular vesicle liquid dispersion specimens comprising the steps of: emitting a laser modulated by a modulation frequency onto each specimen; capturing a temporal signal from laser light backscattered by each specimen for a plurality of temporal periods of a predetermined duration for each specimen; calculating specimen DCT or Wavelet transform coefficients from the captured signal for each of the temporal periods; using the calculated coefficients to pre-train the machine learning classifier; wherein the method further comprises the steps of: using a laser emitter having a focusing optical system coupled to the emitter to emit a laser modulated by a modulation frequency onto the sample; using a light receiver to capture a signal from laser light backscattered by the sample for a plurality of temporal periods of a predetermined duration; calculating sample DCT or Wavelet transform coefficients from the captured signal for each of the temporal periods; using the pre-trained machine learning classifier to classify the calculated sample coefficients as having, or not having, extracellular vesicles present.
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公开(公告)号:EP3903076A2
公开(公告)日:2021-11-03
申请号:EP19838971.0
申请日:2019-12-20
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5.
公开(公告)号:EP3794332A1
公开(公告)日:2021-03-24
申请号:EP19766100.2
申请日:2019-07-31
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6.
公开(公告)号:EP3765833A1
公开(公告)日:2021-01-20
申请号:EP19806055.0
申请日:2019-10-31
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