Machine learning to help in Patient Admissions

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Machine learning

The advent of artificial intelligence, machine learning, anf internet of things has been a revolutionary precept for the several industries. The medical sector has also gained value from the gifts and boons served by these technological feats, and hence, these internet-enabled technologies are being continuously improved and evolved. Machine learning is a sub-domain of artificial intelligence and has become a watchword for global organsations, companies, and industries. This owes to the fact that Machine Learning can help in making processes swift, agile, and more diversely applicable. The use of machine learning in electronic health records has been a tremendous advantage for the medical sector, and now, this technology can also help in categorising as to which patients deserve the highest level of care and attention.

Monitoring Health Risks

PLOS Medical Journal published a research that portrays that machine learning could help doctors and medical experts in evaluating the severity of risks associated with patients’ health. This could in turn help in deciding which patients deserve to be admitted to hospitals at the earliest. The pioneers of the research stated that they wanted to develop a tool that could facilitate better monitoring of health risks in patients.

Future of Research

The electronic records were combined with medications, lifestyle factors, and other dynamics to develop an error-free system for knowing patients’ admission urgency. It is expected that the research will go a long way in improving the overall efficiency and effectiveness of the healthcare industry.

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