Detection of iron deficiency anemia by medical images: a comparative study of machine learning algorithms

Abstract

Background Anemia is one of the global public health problems that affect children and pregnant women. Anemia occurs when the level of red blood cells within the body decreases or when the structure of the red blood cells is destroyed or when the Hb level in the red blood cell is below the normal threshold, which results from one or more increased red cell destructions, blood loss, defective cell production or a depleted sum of Red Blood Cells. Methods The method used in this study is divided into three phases: the datasets were gathered, which is the palm, pre-processed the image, which comprised; Extracted images, and augmented images, segmented the Region of Interest of the images and acquired their various components of the CIE L*a*b* colour space (also referred to as the CIELAB), and finally developed the proposed models for the detection of anemia using the various algorithms, which include CNN, k-NN, Nave Bayes, SVM, and Decision Tree. The experiment utilized 527 initial datasets, rotation, flipping and translation were utilized and augmented the dataset to 2635. We randomly divided the augmented dataset into 70%, 10%, and 20% and trained, validated and tested the models respectively. Results The results of the study justify that the models performed appropriately when the palm is used to detect anemia, with the Naïve Bayes achieving a 99.96% accuracy while the SVM achieved the lowest accuracy of 96.34%, as the CNN also performed better with an accuracy of 99.92% in detecting anemia. Conclusions The invasive method of detecting anemia is expensive and time-consuming; however, anemia can be detected through the use of non-invasive methods such as machine learning algorithms which is efficient, cost-effective and takes less time. In this work, we compared machine learning models such as CNN, k-NN, Decision Tree, Naïve Bayes, and SVM to detect anemia using images of the palm. Finally, the study supports other similar studies on the potency of the Machine Learning Algorithm as a non-invasive method in detecting iron deficiency anemia.

Iron Deficiency Anemia Detection using Machine Learning Models: A Comparative Study of Fingernails, Palm and Conjunctiva of the Eye Images.

“…A new device for image capture was proposed based on the use of the k-Nearest Neighbor (k-NN) algorithm, which achieved 90.26% accuracy using nonanemic images of 84 patients and anemic images of 29 patients. [6] stated that the use of the conjunctiva alone to detect anemia in children is not enough, as exposing the conjunctiva could expose them to germs, bacteria, or falling objects; hence, the use of the palpable palm was recommended.…”

“…Furthermore, since most studies used the conjunctiva of the eyes, this study compared the performance of the conjunctiva of the eyes, palpable palm and colour of the fingernails in the detection of anemia. This is because exposure of the conjunctiva of children may be exposed to infections or falling objects and the palm is also one of the important points of the human body for the detection of anemia [6], [24], hence the need to compare its performance (conjunctiva of the eyes, palpable palm, and colour of the fingernails) performance in the detection of anemia.…”

“…Additionally, minors' eyes would be opened to take pictures or examine the conjunctiva of the eyes directly. There is a chance that someone's finger could get in their eyes [6]. This can be a potential infection source.…”

“…Anemia can also occur when the Hb level in the red blood cell is below the normal threshold, which results from one or more increased red cell destruction, blood loss, defective cell production or a depleted sum of Red Blood Cells [6]. Early detection symptoms of anemia are an ideal primary stage to alleviate it because if the detection and treatment of anemia are delayed, it irreversibly damage the human organ, which can lead to death in some instances [7].…”

Iron deficiency anemia detection using machine learning models: A comparative study of fingernails, palm and conjunctiva of the eye images

“…Anemia can also occur when the Hb level in the red blood cell is below the normal threshold, which results from one or more increased red cell destruction, blood loss, defective cell production or a depleted sum of red blood cells. 7 Early detection symptoms of anemia are an ideal primary stage to alleviate it because if the detection and treatment of anemia are delayed, it irreversibly damages the human organ, which can lead to death in some instances. 8 Hb carries oxygen from the lungs to tissues, and carbon dioxide is returned from the tissue of the lungs, which is considered to be an essential task in the human body.…”