Sökning: "Explainable AI"

Visar resultat 1 - 5 av 41 uppsatser innehållade orden Explainable AI.

  1. 1. Explainable Machine Learning for Lead Time Prediction : A Case Study on Explainability Methods and Benefits in the Pharmaceutical Industry

    Master-uppsats, KTH/Hållbar produktionsutveckling (ML)

    Författare :Paul Fussenegger; Niklas Lange; [2022]
    Nyckelord :Lead time; machine learning; explainability; regression analysis; production planning and control; Ledtid; maskininlärning; förklarbarhet; regressionsanalys; produktionsplanering och produktionsstyrning;

    Sammanfattning : Artificial Intelligence (AI) has proven to be highly suitable for a wide range of problems in manufacturing environments, including the prediction of lead times. Most of these solutions are based on ”black-box” algorithms, which hinder practitioners to understand the prediction process. LÄS MER

  2. 2. CondBEHRT: A Conditional Probability Based Transformer for Modeling Medical Ontology

    Master-uppsats, Högskolan i Halmstad/Akademin för informationsteknologi

    Författare :Linus Lerjebo; Johannes Hägglund; [2022]
    Nyckelord :Artificial Intelligence; Explainable AI; Machine Learning; Deep Learning; Data Mining; Electronic Health Records; Transformer; Graph Neural Network; Natural Language Processing; Hypertension; Kidney Disease; Heart Failure; Medical Ontology;

    Sammanfattning : In recent years the number of electronic healthcare records (EHRs)has increased rapidly. EHR represents a systematized collection of patient health information in a digital format. EHR systems maintain diagnoses, medications, procedures, and lab tests associated with the patients at each time they visit the hospital or care center. LÄS MER

  3. 3. Increasing the Trustworthiness ofAI-based In-Vehicle IDS usingeXplainable AI

    Uppsats för yrkesexamina på avancerad nivå, Mittuniversitetet/Institutionen för informationssystem och –teknologi

    Författare :Hampus Lundberg; [2022]
    Nyckelord :Intrusion Detection System; In-Vehicle Intrusion Detection System; Machine Learning; Deep Learning; Explainable Artificial Intelligence; Trustworthiness.;

    Sammanfattning : An in-vehicle intrusion detection system (IV-IDS) is one of the protection mechanisms used to detect cyber attacks on electric or autonomous vehicles where anomaly-based IDS solution have better potential at detecting the attacks especially zero-day attacks. Generally, the IV-IDS generate false alarms (falsely detecting normal data as attacks) because of the difficulty to differentiate between normal and attack data. LÄS MER

  4. 4. Using XAI Tools to Detect Harmful Bias in ML Models

    Kandidat-uppsats, Umeå universitet/Institutionen för datavetenskap

    Författare :Klaus Virtanen; [2022]
    Nyckelord :Explainable AI; XAI; Machine Learning; Bias; Bias in Machine Learning; LIME; SHAP;

    Sammanfattning : In the past decade, machine learning (ML) models have become farmore powerful, and are increasingly being used in many important contexts. At the same time, ML models have become more complex, and harder to understand on their own, which has necessitated an interesting explainable AI (XAI), a field concerned with ensuring that ML and other AI system can be understood by human users and practitioners. LÄS MER

  5. 5. Visual mapping in AI interfaces: to establish trust in explainable AI in mammography

    Master-uppsats, Mälardalens universitet/Akademin för innovation, design och teknik

    Författare :Ebba Bergström; [2022]
    Nyckelord :Information design; Visual communication; Artificial intelligence; Mammography;

    Sammanfattning : Artificial intelligence (AI) is a broad topic that many researchers and stakeholders want to implement into their daily tasks. There are expectations to implement AI in hospitals, starting with mammography centers. But there is a need to guarantee that it will be efficient and safe to use, and that requires a lot of research. LÄS MER