Automated Machine Learning: Simply Explained!

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👉 Machine Learning in Healthcare & Neurology - Trends

🔹 Automated Machine Learning (AutoML)
To make machine learning techniques easier to apply and to reduce the demand for human experts, automated machine learning (AutoML) has emerged as a growing field that seeks to automatically select, compose, and parametrize machine learning models, so as to achieve optimal performance on a given task and/or dataset.

The aim of autoML is to take advantage of complexity in the underlying data set to help guide and identify the most appropriate model (and their associated hyperparameters), optimizing performance, whilst simultaneously attempting to maximize the reliability of resulting predictions

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🎓 About AINeuroCare

An educational platform for the next decade of digital clinical care. Teaching clinicians about:

Ⓐ Artificial Intelligence in Healthcare
Ⓓ Digital Health (Telehealth, mHealth)
Ⓥ Value-Based Care
Ⓝ Neurological Care of the future (AI, Digital, Value-Based)

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👨‍🎓 About Junaid Kalia MD, BCMAS

✓ Digital Health Strategist: Virtual Care strategist and implementation specialist.
✓ AIinHealthcare Expertise: Design and clinically test AI in Healthcare products. Consult on clinical & non-clinical AI applications in healthcare.
✓ Clinical Neurologist In-person and Telehealth: Neurology, Epilepsy, Stroke, Neurocritical Care, Neurohospitalist, Teleneurologist, Telestroke, Teleneurointensevist.

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Tags: #machinelearning #AutoML #AutomatedML #Data #Predictionmodel #Modelbuilding

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Disclaimer:
For Education purposes only. The advice does not relate to clinical decision-making on specific patients. Discussion of non-FDA-approved products may be included.