Sökning: "word-similarity"

Hittade 3 uppsatser innehållade ordet word-similarity.

  1. 1. Discovering Implant Terms in Medical Records

    Kandidat-uppsats, Linköpings universitet/Institutionen för datavetenskap

    Författare :Oskar Jerdhaf; [2021]
    Nyckelord :AI; Machine Learning; Medical Records; Patient Records; Medical; Record; Electronic Records; Electronic Medical Records; BERT; EMR; Implant Terms; Implants; Term; Terms; Term Discovery; Artificial Intelligence; Word; Similarity; Word Similarity; word-similarity; embeddings; word embeddings; word-embeddings; transformers; KDTREE; BALLTREE; NER; AI; Artificiel Intelligens; Maskininlärning; Patient Journal; Medicinsk Journal; Elektronisk Medicinsk Journal; Termer; BERT; KDTREE; BALLTREE; NER; liknande ord; transformers; EMR;

    Sammanfattning : Implant terms are terms like "pacemaker" which indicate the presence of artifacts in the body of a human. These implant terms are key to determining if a patient can safely undergo Magnetic Resonance Imaging (MRI). LÄS MER

  3. 2. A retrieval-based chatbot ́s opinion on the trolley problem

    Kandidat-uppsats,

    Författare :Hampus Björklin; Tim Abrahamsson; Oscar Widenfalk; [2021]
    Nyckelord :chatbot; language model; trolley problem; BERT encoding; discord;

    Sammanfattning : The goal of this project was to create a chatbot capable of debating a user using limited resources including a discussion thread from the online debate forum Kialo. A retrieval based bot was designed and the discussion thread was converted into a database which the bot could interpret and choose an appropriate answer from. LÄS MER

  4. 3. Finding Synonyms in Medical Texts : Creating a system for automatic synonym extraction from medical texts

    Kandidat-uppsats, Linköpings universitet/Institutionen för datavetenskap

    Författare :Gustav Cederblad; [2018]
    Nyckelord :eHealth; distributional semantics; medical synonyms; semantic relations; word similarity;

    Sammanfattning : This thesis describes the work of creating an automatic system for identifying synonyms and semantically related words in medical texts. Before this work, as a part of the project E-care@home, medical texts have been classified as either lay or specialized by both a lay annotator and an expert annotator. LÄS MER