DIAGNOSING HYPOADRENOCORTICISM FROM HEMATOLOGIC AND SERUM CHEMISTRY PARAMETERS USING MACHINE LEARNING ALGORITHM

摘要

The invention is directed to a hypoadrenocorticism diagnostic tool including a computer device for executing a trained machine learning algorithm to analyze bloodwork parameters and determine a hypoadrenocorticism diagnosis based on the bloodwork parameters. The bloodwork parameters may include complete blood count and serum chemistry parameters. The computer device receives the bloodwork parameters associated with a patient and analyzes the bloodwork parameters using the trained machine learning algorithm. The computer device determines the hypoadrenocorticism diagnosis indicating whether the patient is positive or negative for hypoadrenocorticism using the trained machine learning algorithm, and displays the hypoadrenocorticism diagnosis on a graphical user interface.