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B l o g A r t i c l e Future LABELING: Data Digitization, Structure and Automation Labeling process prominence has increased over the years and manufacturers are trying to manage product labeling & artwork at the same time while maintaining end-to-end life cycle changes of product labeling. In the current scenario, labeling can be in various forms, both physical and digital as well. Controlling the labeling content becomes difficult as it comes from diverse sources and all these content changes during the product lifecycle process is a daunting task for labeling teams. Labeling Automation can help ease these challenges. Automation & AI Artificial Intelligence is involved in various domains like education, retail marketing & healthcare sector, etc. To that, data labeling is a vital aspect in the healthcare domain (Pharmaceutical industry) with its keen specifications predefined by the health regulatory authorities (HRA). Systems need to understand what is shown on the display part such as images, symbols, written text & among many other things. Medical labeling is an imperative or integral stage of data preprocessing in supervised learning (machine learning) process. Historical data with predefined target attributes (values) is used for this process model. Data Organization and Structure Organizations look forward to collaboration so that all the data is available at the source thus enabling them to keep a check on the labeling content. To ensure this control, e-labeling has already entered the market and with time it is taking up much of the space in the life science industry. Read Full Article www.DDIsmart.com