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      Deep Learning-Assisted Segmentation and Classification of Brain Tumor Types on Magnetic Resonance and Surgical Microscope Images

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      World Neurosurgery
      Elsevier BV

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          Abstract

          The primary aim of this research was to harness the capabilities of deep learning to enhance neurosurgical procedures, focusing on accurate tumor boundary delineation and classification. Through advanced diagnostic tools, we aimed to offer surgeons a more insightful perspective during surgeries, improving surgical outcomes and patient care.

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          Using Bayesian Model Averaging to Calibrate Forecast Ensembles

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            Artificial Intelligence in Surgery

            The aim of this review was to summarize major topics in artificial intelligence (AI), including their applications and limitations in surgery. This paper reviews the key capabilities of AI to help surgeons understand and critically evaluate new AI applications and to contribute to new developments.
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              A few useful things to know about machine learning

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                Author and article information

                Contributors
                Journal
                World Neurosurgery
                World Neurosurgery
                Elsevier BV
                18788750
                February 2024
                February 2024
                : 182
                : e196-e204
                Article
                10.1016/j.wneu.2023.11.073
                38030068
                43ebaf05-8fda-41ca-a22b-ba1d5da81ae1
                © 2024

                https://www.elsevier.com/tdm/userlicense/1.0/

                https://doi.org/10.15223/policy-017

                https://doi.org/10.15223/policy-037

                https://doi.org/10.15223/policy-012

                https://doi.org/10.15223/policy-029

                https://doi.org/10.15223/policy-004

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