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In Medical journal, Armed Forces India

Currently, most critical care information is not expressed automatically at a granular level, rather is continually assessed by overindulged Intensive Care Unit (ICU) staff. Furthermore, due to different confounding morbidities and the uniqueness of the ICU setting, it is difficult to protocolize treatment regimens in the ICU. In highly complex ICU setting where man and resource management becomes extremely challenging, definite advancements are required to implement Artificial Intelligence (AI) for prognosticating the course of the disease to aid in informed decision-making. AI is the intelligence of a computer or computer-supervised robot to execute a piece of work commonly associated with intelligent beings, wherein the machines go beyond the realms of normal information processing by adding the characteristics of learning, sound reasoning, and weighting of the inputs. AI recognizes circuitous, relational time-series blueprint within datasets and this reasoning of analysis transcends conventional threshold-based analysis adapted in ICU protocols. AI works on the principle of a more complex form of Machine Learning by Artificial Neural Networks (ANN). These information-processing paradigms use multidimensional arrays called tensors which aid in 'learning' and 'weighting' all the information made available to it, thereby converting normal machine learning into Deep Learning. Here, the use of AI for data mining in complex ICU settings for protocol formulation and temporal representation and reasoning is discussed.

Datta Rashmi, Singh Shalendra


Artificial intelligence, Critical care, Intensive care unit