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Showing 1 to 4 of 4 for “"super learner"”.

  1. Integrating LLMs and Causal Inference: Comparing Oral Anticoagulant Effects on Thrombosis Recurrence, Bleeding Risk and Death Using MIMIC-IV Data

    … combined with structured fields and passed to a Super Learner formed from non-parametric, semi-parametric and tree learners. The ensemble attained the lowest negative log-likelihood (NLL) when predicting major bleeding and thrombosis recurrence within 3 and 6 months and mortality within 12 …

    chapman Repository record for Integrating LLMs and Causal Inference: Comparing Oral Anticoagulant Effects on Thrombosis Recurrence, Bleeding Risk and Death Using MIMIC-IV Data (opens in a new tab)

  2. Artificial intelligence in business analytics, capturing value with machine learning applications in financial services

    … for data-driven decision making. The focus is on supervised binary classification on structured datasets, which are vastly present in relational databases across all enterprises. Advanced analytics has become indispensable for today's corporate world and it is demonstrated that predictive …

    strathclyde Repository record for Artificial intelligence in business analytics, capturing value with machine learning applications in financial services (opens in a new tab)

  3. Anticoagulant Treatment Effects Assessment in Antiphospholipid Syndrome Patients Using Targeted Learning and the Oracle Health EHR Data

    … maximum likelihood estimation (TMLE) with Super Learner techniques. My primary focus was on the difference in one-year all-cause mortality risk, but I also looked at long-term outcomes up to five years and examined differences across various patient subgroups. </p> <p>The results indicated …

    chapman Repository record for Anticoagulant Treatment Effects Assessment in Antiphospholipid Syndrome Patients Using Targeted Learning and the Oracle Health EHR Data (opens in a new tab)

  4. Anomalous behaviour detection for cyber defence in modern industrial control systems

    … sectors. Next, this research introduces a novel super learner ensemble anomaly detection and cyber risk quantification framework to profile anomalous behaviour in ICS and derive a cyber risk score. The proposed framework and associated learning models are experimentally validated. The produced …

    wlv Repository record for Anomalous behaviour detection for cyber defence in modern industrial control systems (opens in a new tab)