Anaemia Estimation for Patients Using Lasso And Ridge Regression Algorithms

Ambika B J, Nirmala S Guptha, Syeda Ayesha Siddiqha — Mon, 04 Dec 2023 00:00:00 +0000

Treatment Suggested by computer opinion is valuable in medical decision-making, saves time, is more accurate, and doesn't require hiring new workers. Numerous nutritional assessments reveal that roughly 25% of people worldwide are anaemic. A machine learning regression that can accurately detect anaemic is therefore urgently needed. To recognise anaemic, it is important to know which classifier, or combination of classifiers, produces the best level of delicacy in the classification of red blood cells. To determine and compute the anaemic, we employed the Lasso and Ridge regressions. However, the Ridge classifier outperforms the Lasso regression and reaches a higher level of delicacy. Consequently, a better and more significant method should be applied to obtain the greatest degree of finesse in medicine.

Milestone Transactions on Medical Technometrics

Anaemia Estimation for Patients Using Lasso And Ridge Regression Algorithms