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Patient Selection for Diabetes Drug Testing Applying AI to Wearable Device Data By the end of the course, you will have the skills to analyze an EHR dataset, transform it to the right level, build powerful features with TensorFlow, and model the uncertainty and bias with TensorFlow Probability and Aequitas. You will cover EHR data privacy and security standards, how to analyze EHR data and avoid common challenges, and cover key industry code sets. Learn the fundamental skills to work with EHR data and build and evaluate compliant, interpretable models. Hippocampus Volume Quantification for Alzheimer’s Progression Applying AI to EHR Data Design and apply machine learning algorithms to solve the challenging problems in 3D medical imaging and how to integrate the algorithms into the clinical workflow. Discover how clinicians use 3D medical images in practice and where AI holds most potential in their work with these images. Understand how these images are acquired, stored in clinical archives, and subsequently read and analyzed. Learn the fundamental skills needed to work with 3D medical imaging datasets and frame insights derived from the data in a clinically relevant context. Pneumonia Detection from Chest X-Rays Applying AI to 3D Medical Imaging Data Build different AI models for different clinical scenarios that involve 2D images and learn how to position AI tools for regulatory approval. Extract 2D images from DICOM files and apply the appropriate tools to perform exploratory data analysis on them. Learn the fundamental skills needed to work with 2D medical imaging data and how to use AI to derive clinically-relevant insights from data gathered via different types of 2D medical imaging such as x-ray, mammography, and digital pathology. Intermediate Python, and Experience with Machine Learning Applying AI to 2D Medical Imaging Data Finally, build an algorithm that uses data collected from wearable devices to estimate the wearer’s pulse rate in the presence of motion. 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. Learn to build, evaluate, and integrate predictive models that have the power to transform patient outcomes.

Get access to the classroom immediately on enrollment Prerequisites Intermediate Python, and Experience with Machine Learning What You Will Learn AI for Healthcare

Free download CyberLink AudioDirector Ultra 2024 v14.0.3325.0