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AutoML-engineering
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AutoML-engineering
60 followers · 344 following

Achievements

Achievement: Pull Sharkx2Achievement: QuickdrawAchievement: Arctic Code Vault Contributor

Achievements

Achievement: Pull Sharkx2Achievement: QuickdrawAchievement: Arctic Code Vault Contributor

Highlights

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Google Scholar Research Papers

  1. (Co-Author)Provost, S. with Tighe, D., Ho, M., Puglia, F., McMahon, J., 2023. Risk Adjusted Cumulative Sum chart methodology to monitor of free flap failure rates in the QOMS national audit. British Journal of Oral and Maxillofacial Surgery VOLUME 61, ISSUE 10, E5.

  2. (Co-Author)Provost, S. with Tighe, D., Sasson, I., Ho, M., 2023. Technical appendix-Validating risk-adjustment models used in QOMS. British Journal of Oral and Maxillofacial Surgery (QOMS).

  3. (Co-Author)Provost, S. with Tighe, D., McMahon, J., Schilling, C., Ho, M., and Freitas, A., 2022. Machine learning methods applied to risk adjustment of cumulative sum chart methodology to audit free flap outcomes after head and neck surgery. British Journal of Oral and Maxillofacial Surgery, 60(10), pp.1353-1361.

  4. (Co-Author)Provost, S. with Tighe, D., Tekeli, K., Gouk, T., Smith, J., Ho, M., Moody, A., and Walsh, S., Freitas, A., 2023. Machine learning methods applied to audit of surgical margins after curative surgery for facial (non-melanoma) skin cancer. British Journal of Oral and Maxillofacial Surgery, 61(1), pp.94-100.

Medium Blogs

Medium Blogs

  1. Provost, S., Introduction to Automated Machine Learning with Auto-Sklearn ⚙️.

  2. Provost, S., Diversity and a novel Deep Learning model called Deep Forest: Applying an Important Concept to a Promising Framework.

  3. Provost, S., Classification of Sleep-Wake states with the use of a novel Deep-Learning approach.

  4. Provost, S., Michele, L., Classification of Sleep-Wake states with the use of a novel Deep-Learning approach.

  5. Provost, S., Michele, L., Computer Science Students take a step in the sleep-medicine field with Actigraphy.

  6. More can be seen here.

Pinned Loading

  1. Auto-Sklong Auto-Sklong Public

    Auto-Scikit-Longitudinal (Auto-Sklong) is an automated machine learning (AutoML) library designed to analyse longitudinal data (Classification tasks focussed as of today) using various search metho…

    Python 10

  2. scikit-longitudinal scikit-longitudinal Public

    Scikit-longitudinal (Sklong) is an open-source Python library & Scikit-Learn API compliant, tailored to longitudinal machine learning classification tasks. It is ideal for researchers, data scienti…

    Python 15 1

  3. scikit-lexicographical-trees scikit-lexicographical-trees Public

    Forked from neurodata/scikit-learn

    scikit-lexicographical-trees: Based upon Scikit-Learn(-tree), it offers adapted trees and forest for Longitudinal Classification

    Python 2

  4. gama gama Public

    Forked from openml-labs/gama

    An automated machine learning tool aimed to facilitate AutoML research.

    Python 1