Healthcare IT Today: Analytics & Big Data

In healthcare, big data analytics involves integration and analysis of large amounts of highly heterogeneous data, such as genomic information, pharmacogenomics, metagenomics, proteomics, metabolic engineering, interactomics, personalized medicine, and diseasomics, biomedicine data, and electronic health information data. To get valuable information from this data, it must be properly managed and analyzed. Otherwise, coming up with a solution through studying vast data is akin to looking for a needle in a haystack. From diagnostic imaging and chronic illness management to demographic health and personalized medicine, analytics & big data technologies have shown promise in improving a variety of areas of care. To make sense of this massive volume of data, AI-based (AI) algorithms and unique fusion techniques would be required. Overcoming challenges of bias, safety and confidentiality, and user trust will be critical for the effective application of these models in patient care, as healthcare institutions increasingly rely on big data and analytics technologies for increased insights and streamlined treatment operations.