Benefit of machine learning for patient care in future – ZMR Blog
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Benefit of machine learning for patient care in future

Machine learning and Artificial Intelligence are the two new concepts that are being applied in a number of areas owing to their increasing benefits and positive outcomes. They are used in every single phase of our lives nowadays. Thus, keeping this in mind, the scientists from the MIT’s Computer Science and AI Labs have come up with a new option to help the doctors take the right decisions. The researchers have used the machine learning techniques in healthcare recently and published it in a paper so as to prove their concept is foolproof.

During the patients care, a doctor has to manage a lot of charts, test results, prescriptions, scanned sheets, and so on in order to keep all the information and details regarding the individual so as to diagnose and prognose. The doctors have a number of patients visiting them on a daily basis; hence, keeping a track of massive amount of details for the analysis is a complicated and life threatening job to perform. If the documentation errors occur during the patients’ consultation then it makes it even harder for the doctors to take a sound decision and carry out the right real-time treatment during the situation.

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For including the machine learning program into healthcare, the researchers used a number of medical data that too of different types, for instance, the electronic health records, to predict the present or the future outcomes. One machine learning approach is the “ICU intervene” so as to make it simpler and easier for the doctors to keep all the vital sign, demographics, lab notes, and other critical ICU data intact under a single umbrella. The prediction of treatment required for the different symptoms and patients gets all the more quick. This technology is an aid for the doctors in the ICU as the environment is very intense and stressful in there. The chances of improvement in the healthcare and intervention predictability are also enhanced.

Another approach is the “EHR Model Transfer” wherein the application of the predictive models on the electronic health record (EHR) system is enabled in spite of the data being collected from different EHR systems. The prediction model utilization to predict the prolonged length of stay or mortality through the system can prove fruitful in the long run.

Both these systems were created using the data obtained from crucial care database “MIMIC” that has the critical data of about 40000 patients and is one of the developments of the MIT Lab for Computational Physiology.

Thus, it looks like machine learning and artificial intelligence can change the gaming pattern in the healthcare sector in the near future.

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