Healthcare

AI in healthcare services

Healthcare

AI can enhance preventive care and quality of life, as well as producing more accurate diagnosis and treatment regimens based on patient's past history of illness and variety of other attributes by making clinical and operational decisions faster. By examining data, healthcare, and other sources, AI models can help anticipate and predict new diseases and track existing illness and their effects. delivering improved patient care.

Use Cases
Data Insights

Patient care and operations management data can both benefit from data analysis. The outcome of the analysis aid in improving clinical care, increasing illness prevention, and determining the efficacy of various treatment choices.

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Derive meaningful data from unstructured data

Extract meaningful data from raw or unstructured data and analyse them using machine learning and natural language processing making it accessible and usable to businesses in a meaningful way.

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Identify new relationships from the patient information.

Identify new relationships from data by analysing patients' health records and conversations with doctors, and provide recommendations based on the data analysed, as well as summarising the conversation and other medical information in a user understandable format.

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Research and Publications
Multilingual Text Inversion Detection using Shape Context' in the IEEE TENSYMP 2021 held at Jeju, Korea.

It is common to have aberrations in manually scanned textual documents. Document inversion is among the most frequent but a harder anomaly to detect efficiently. Moreover, an algorithm that may detect text inversion in one language may not work ...

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From Admission to Discharge, How Artificial Intelligence Could Optimize Patient Care : A Brief Review

The applications of artificial intelligence (AI) in healthcare have been steadily growing over the past few years. This is largely due to the availability of large amounts of healthcare data, coupled with a dramatic increase in computational power.

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