SwePub
Sök i LIBRIS databas

  Utökad sökning

L773:1661 3791 OR L773:1661 3805
 

Sökning: L773:1661 3791 OR L773:1661 3805 > (2020-2023) > Natural Language Pr...

Natural Language Processing to Extract Meaningful Information from a Corpus of Written Knowledge in Breast Cancer : Transforming Books into Data

Catanuto, Giuseppe (författare)
GRETA Grp Reconstruct & Therapeut Adv, Milan, Italy.;Humanitas Ctr, Breast Surg Unit, Catania, Italy.
Rocco, Nicola (författare)
GRETA Grp Reconstruct & Therapeut Adv, Milan, Italy.;Univ Naples Federico II, Dept Adv Biomed Sci, Naples, Italy.
Balafa, Konstantina (författare)
Humanitas Ctr, Breast Surg Unit, Catania, Italy.
visa fler...
Masannat, Yazan (författare)
NHS Grampian, Aberdeen Royal Infirm, Breast Unit, Aberdeen, Scotland.
Karakatsanis, Andreas (författare)
Uppsala universitet,Endokrinkirurgi,Uppsala Univ Hosp Akademiska, Dept Surg, Sect Breast Surg, Uppsala, Sweden.
Maglia, Anna (författare)
GRETA Grp Reconstruct & Therapeut Adv, Milan, Italy.
Barry, Peter (författare)
Univ Catania, Dept Drug & Hlth Sci, Catania, Italy.
Pappalardo, Francesco (författare)
Royal Marsden NHS Fdn Trust, Dept Breast Surg, Sutton, England.
Nava, Maurizio Bruno (författare)
GRETA Grp Reconstruct & Therapeut Adv, Milan, Italy.
Caruso, Francesco (författare)
Humanitas Ctr, Breast Surg Unit, Catania, Italy.
visa färre...
GRETA Grp Reconstruct & Therapeut Adv, Milan, Italy;Humanitas Ctr, Breast Surg Unit, Catania, Italy. GRETA Grp Reconstruct & Therapeut Adv, Milan, Italy.;Univ Naples Federico II, Dept Adv Biomed Sci, Naples, Italy. (creator_code:org_t)
S. Karger AG, 2023
2023
Engelska.
Ingår i: Breast Care. - : S. Karger AG. - 1661-3791 .- 1661-3805. ; 18:3, s. 209-212
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Introduction: Books and papers are the most relevant source of theoretical knowledge for medical education. New technologies of artificial intelligence can be designed to assist in selected educational tasks, such as reading a corpus made up of multiple documents and extracting relevant information in a quantitative way.Methods: Thirty experts were selected transparently using an online public call on the website of the sponsor organization and on its social media. Six books edited or co-edited by members of this panel containing a general knowledge of breast cancer or specific surgical knowledge have been acquired. This collection was used by a team of computer scientists to train an artificial neural network based on a technique called Word2Vec.Results: The corpus of six books contained about 2.2 billion words for 300d vectors. A few tests were performed. We evaluated cosine similarity between different words.Discussion: This work represents an initial attempt to derive formal information from textual corpus. It can be used to perform an augmented reading of the corpus of knowledge available in books and papers as part of a discipline. This can generate new hypothesis and provide an actual estimate of their association within the expert opinions. Word embedding can also be a good tool when used in accruing narrative information from clinical notes, reports, etc., and produce prediction about outcomes. More work is expected in this promising field to generate "real-world evidence." (c) 2023 S. Karger AG, Basel

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Språkteknologi (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Language Technology (hsv//eng)
NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Nyckelord

Breast cancer
Artificial intelligence
Medical education

Publikations- och innehållstyp

ref (ämneskategori)
art (ämneskategori)

Hitta via bibliotek

Till lärosätets databas

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy