A method of determining a presence of appendicitis in a patient, the method comprising computer implemented steps of: receiving a medical image associated with the patient, wherein the medical image comprises an appendix of the patient; determining, using at least one trained machine learning model, an anatomical position of the appendix in the medical image, wherein the step of determining the anatomical position of the appendix includes identifying a contour associated with the appendix in the medical image based on pixel information of the medical image; wherein the step of determining the anatomical position of the appendix includes determining an orientation of the appendix in the body of the patient, and wherein the determined orientation of the appendix is one of the following orientations: anterior, retrocecal, post-ileal, paracecal, posterior, subcecal, pelvic, or promontoric; determining, using the at least one trained machine learning model, a dimension associated with the appendix in the medical image, the dimension being determined based on the identified contour of the appendix; identifying, using the at least one trained machine learning model, if the dimension associated with the appendix is above a pre-defined threshold; and generating a notification on an output unit if the dimension associated with the appendix is above the pre-defined threshold, wherein dimension associated with the appendix being above the pre-defined threshold indicates presence of appendicitis in the patient; wherein generating the notification includes generating an alert on a user interface of the output device; wherein the alert includes the contour associated with the appendix in the medical image which contour is highlighted to indicate that the dimension associated with the appendix is above the pre-defined threshold. receiving a medical image associated with the patient, wherein the medical image comprises an appendix of the patient; determining, using at least one trained machine learning model, an anatomical position of the appendix in the medical image, wherein the step of determining the anatomical position of the appendix includes identifying a contour associated with the appendix in the medical image based on pixel information of the medical image; wherein the step of determining the anatomical position of the appendix includes determining an orientation of the appendix in the body of the patient, and wherein the determined orientation of the appendix is one of the following orientations: anterior, retrocecal, post-ileal, paracecal, posterior, subcecal, pelvic, or promontoric; determining, using the at least one trained machine learning model, a dimension associated with the appendix in the medical image, the dimension being determined based on the identified contour of the appendix; identifying, using the at least one trained machine learning model, if the dimension associated with the appendix is above a pre-defined threshold; and generating a notification on an output unit if the dimension associated with the appendix is above the pre-defined threshold, wherein dimension associated with the appendix being above the pre-defined threshold indicates presence of appendicitis in the patient; wherein generating the notification includes generating an alert on a user interface of the output device; wherein the alert includes the contour associated with the appendix in the medical image which contour is highlighted to indicate that the dimension associated with the appendix is above the pre-defined threshold.