In the age of artificial intelligence and machine learning, the standards for data quality have risen but machine learning can aid in cleansing and enriching data. In this webinar, Tamas Foldi, Starschema CTO and Tableau Zen Master presents the latest trends in data quality and enrichment and demonstrates how AI is helping to make cleaning and enriching data easier.
Cardiac Resynchronization Therapy (CRT) can be a life-saving therapeutic option. However, the intervention itself has considerable risks, carries significant expense and its benefits to heart failure patients are limited to a small group of suitable patients, making patient selection critical. The right algorithm can determine patient selection criteria to identify patients most likely to benefit from CRT and least likely to suffer pre-operative or post-operative complications.
Magnetic resonance imaging (MRI) artifacts, distortions or false signals that affect image quality, may adversely affect diagnostic quality, resulting in potential diagnostic errors and the need for costly and time consuming repeat examinations that may delay timely treatment. Detecting these artifacts with convolutional neural networks can save costs and improve outcomes.