An AI based digital pathology decision support tool to identify and classify lung cancer.

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CONTEXTVISION AB

AI baserade mjukvara - beslutstödsverktyg (DST) för att bistå lungpatologer vid histopatologist utvärdering av lungbiopsier.

Vår AI baserade mjukvara är tänkt att: 1. ange om cancer finns i vävnadsprovet 2. indikera områden där cancer föreligger i biopsin 3. klassificera dessa områden i olika typer av lungcancer Vid Vinnova projektets slut har vi ännu inte kunnat träna nätverket. Alla lungbiopsier blev färdig-annoterade och kvalitetssäkrade under projekttiden. Nu återstår själva träningen och utvärderingen av resultatet.

Det övergripande målet med projektet var att skapa ett AI-baserat beslutstödsverktyg (DST) för att bistå lungpatologer vid histopatologist utvärdering av lungbiopsier.

Läs mer

PROJEKTFAKTA

KATEGORI:

Informatik för diagnostik/Bioinformatik

KOORDINATOR:

CONTEXTVISION AB

PROJEKTNUMMER:

2018-00184

BIDRAG:

995 280 kr

STARTDATUM:

juni 1, 2018

SLUTDATUM:

juni 25, 2019

PROJEKTSTATUS:

Avslutade

NY SÖKNING