Estudio relacionado con nuevas tecnologías de machine Learning para determinar cuadros clínicos. - Macias Vera, Gilda Gisella (2023)
The main problem in the hospitals of the city of Babahoyo is the lack of control and order in the records of patient examinations. This is due to the fact that a large amount of diverse data is handled, such as texts and images, which makes analysis difficult. The disorganization in the records causes incorrect diagnoses to be given, and inappropriate medicines to be prescribed, which can worsen the patients' condition. This represents a negative problem for patients, as they will not receive the proper treatment. As for the contribution of this technology, Machine Learning can help doctors avoid medical errors and improve patient safety. By analyzing data in an accurate and efficient way, Machine Learning algorithms can recognize medical errors and alert doctors so that they can take preventive measures. In conclusion, this tool has great potential to improve medical care by enabling doctors to analyze large data sets and make more informed decisions about the diagnosis and treatment of diseases. Finally, it should be noted that implementing Machine Learning to determine clinical pictures can have significant benefits, but it can also present significant challenges. It is necessary to carefully consider both the advantages and disadvantages of this technology before implementation and take appropriate measures to ensure data quality, patient privacy and safety, and the accuracy and transparency of the Machine Learning model used in healthcare.