Although the use of machine learning in medicine has been extended, but the default is to find patterns in the health records, which is this type of information is not static or recovers regularly. Probe, an investigator of the Carnegie Mellon University developed a transparent and reproducible machine learning tool for facilitate health information analysis. This is herramienta, llamada TL-Lite, can be used in the clinical prediction, with the objective of predict trends in results in individual patients.
Following the study published in Machine learning research proceedings, TL-Lite starts with Data base information visualizations and end with visual risk evaluations of a temporal model. The TL-Lite objective facilitates predictive prognosis and, according to its author Jeremy Weiss, can be used to predict the thrombocytopenia grave during the stages of the Intensive Care Unit (UCI). Also to predict the survival of patients admitted to the UCI one day after the onset and to predict the microvascular complications in patients with type 2 diabetes.
The use of machine learning in medicine has seen a recent eye and in the context of the Covid-19 pandemic, it has been used to address problematic distances. A study published in the magazine Journal of Medical Internet Research propose the use of this technology to examine electronic medical records to better predict patients’ progress with Covid-19.
The models of machine learning, in the context of the health of the health, suele require various dates and large scale, afirma the study published in the year of 2021. It is to be able of replica of the effectiveness of the population with the train trained. When these models are built inside a hospital, they are always effective for other patient populations, because they are trained with dates that are not representative of the entire population. To make sure it is limiting, investigators should try a learning machine called learn federado. This ground has been cleared to allow models to learn from many sources, for example, many hospitals, without exposing patient sensitive data.
In the wake of the pandemic, but also in the area of medicines and therapies, the learning machine also had to be great help. A study published in the magazine Nature communication in February proposes the use of machine learning to identify existing drugs that can be used to combat Covid-19 in adult adults. This is to identify with algorithms the intersection of the genes of the pathway and the pulmonary endowment and the EARS-CoV-2. The next series in a row identify existing medicines what is happening about these genes and perform clinical trials to find out the effectiveness of the most successful candidates.
Burden new technologies great promises advances in medicine, through a automated analysis and accelerated the dates and creation of models, mainly mediating the Machine learning. Although there are many ways to improve, learning machine can be used as a herramienta auxiliar para la clinical prescription and to predict patient progress in patients. In a near future, in accordance with its operation, these products will become extensively used in world health systems.
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