amanjeetsahu/AI-for-Healthcare-Nanodegree
Learn to build, evaluate, and integrate predictive models that have the power to transform patient outcomes. Begin by classifying and segmenting 2D and 3D medical images to augment diagnosis and then move on to modeling patient outcomes with electronic health records to optimize clinical trial testing decisions. Finally, build an algorithm that uses data collected from wearable devices to estimate the wearer’s pulse rate in the presence of motion.
This project helps medical professionals, especially radiologists and clinicians, enhance diagnostic accuracy and optimize patient care using AI. You'll learn to analyze 2D and 3D medical images like X-rays and CT scans to classify diseases and segment anatomical structures. It also covers modeling patient outcomes from electronic health records and estimating pulse rates from wearable device data, ultimately providing predictive models to inform clinical decisions and improve patient outcomes.
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Use this if you are a healthcare practitioner or researcher looking to leverage AI for better medical image analysis, patient outcome prediction, and physiological monitoring.
Not ideal if you are looking for a plug-and-play software application, as this project focuses on building and understanding the underlying AI models.
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May 31, 2020
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