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The AutoML industry is expected to further experience significant growth, driven by rising applications and research in the medical field. As healthcare providers and researchers recognize the potential of AutoML in revolutionizing patient care and medical research, there is a surge in demand for AI-driven solutions tailored to healthcare challenges. AutoML offers the ability to automate complex machine learning tasks, such as model selection and feature engineering to streamline the development of predictive models for disease diagnosis, treatment optimization, and drug discovery.
Furthermore, the ongoing research in AutoML-specific methodologies for medical data analysis is expanding its scope and enhancing its accuracy in healthcare applications. These trends will signal a promising future for AutoML in transforming medical practices and improving patient outcomes. To cite an instance, in August 2023, a study was released for examining the suitability and efficacy of AutoML for prospective uses in diagnostic neuroradiology. The objective was to assess the feasibility and merits of employing AutoML models vis-à-vis traditional machine learning models.