Kaung Myat Naing

• Doctor of Philosophy (Advanced Manufacturing System Engineering)
• Technological University (Dawei)

Anaplasmosis, which is caused by Anaplasma spp. and transmitted by tick bites, is one of the most serious livestock animal diseases worldwide, causing significant economic losses as well as public health issues. Anaplasma marginale, a gram-negative intracellular obligate bacterium, can cause disease in cattle and other ruminants. Because of the ins...

Vector-borne diseases pose a major worldwide health concern, impacting more than 1 billion people globally. Among various blood-feeding arthropods, mosquitoes stand out as the primary carriers of diseases significant in both medical and veterinary fields. Hence, comprehending their distinct role fulfilled by different mosquito types is crucial for...

Traditional mosquito identification methods, relied on microscopic observation and morphological characteristics, often require significant expertise and experience, which can limit their effectiveness. This study introduces a self-supervised learning-based image classification model using the Bootstrap Your Own Latent (BYOL) algorithm, designed to...

Trypanosomiasis, a significant health concern in South America, South Asia, and Southeast Asia, requires active surveys to effectively control the disease. To address this, we have developed a hybrid model that combines deep metric learning (DML) and image retrieval. This model is proficient at identifying Trypanosoma species in microscopic images...

Medical image examination with a deep learning approach is greatly beneficial in the healthcare industry for faster diagnosis and disease monitoring. One of the popular deep learning algorithms such as you only look once (YOLO) developed for object detection is a successful state-of-the-art algorithm in real-time object detection systems. Although...

Trypanosomiasis is a significant public health problem in several regions across the world, including South Asia and Southeast Asia. The identification of hotspot areas under active surveillance is a fundamental procedure for controlling disease transmission. Microscopic examination is a commonly used diagnostic method. It is, nevertheless, primari...

Deep metric learning-based image retrieval systems have recently been used in medical applications because they provide clinically relevant information-based similar images based on prior knowledge. Although train examiners and deep learning models successfully analyze leukocyte cells, there are still numerous difficult challenges due to biological...

Mosquito-borne diseases such as dengue fever and malaria are the top 10 leading causes of death in low-income countries. Control measure for the mosquito population plays an essential role in the fight against the disease. Currently, several intervention strategies; chemical-, biological-, mechanicaland environmental methods remain under developmen...

Trypanosomiasis caused Trypanosoma evansi is current public health concern especially, in south Asia and Southeast Asia. Although polymerase chain reaction is currently used as a standard method, the techniques required skilled personnel, were performed in multiple steps, and required expensive instruments. Fundamental microscopic approach als...

Background Object detection is a new artificial intelligence approach to morphological recognition and labeling parasitic pathogens. Due to the lack of equipment and trained personnel, artificial intelligence innovation for searching various parasitic products in stool examination will enable patients in remote areas of undeveloped countries to acc...

The infection of an avian malaria parasite ( Plasmodium gallinaceum ) in domestic chickens presents a major threat to the poultry industry because it causes economic loss in both the quality and quantity of meat and egg production. Computer-aided diagnosis has been developed to automatically identify avian malaria infections and classify the blood...

This study proposes to evaluate the performance of Acute Myeloid Leukaemia (AML) blast cell detection models in microscopic examination images for faster diagnosis and disease monitoring. One of the popular deep learning algorithms such as You Only Look Once (YOLO) developed for object detection is the successful state-of-the-art algorithms in real...

Recently, mosquito-borne diseases have been a significant problem for public health worldwide. These diseases include dengue, ZIKA and malaria. Reducing disease spread stimulates researchers to develop automatic methods beyond traditional surveillance Well-known Deep Convolutional Neural Network, YOLO v3 algorithm, was applied to classify mosquito...

Background: The infections of an avian malaria parasite (Plasmodium gallinaceum) in domestic chickens presents a major threat to poultry industry because it cause economical loss in both quality and quantity of meat and egg productions. Deep learning algorithms have been developed to identify avian malaria infections and classify its blood stage de...

The infection of an avian malaria parasite ( Plasmodium gallinaceum ) in domestic chickens presents a major threat to the poultry industry because it causes economic loss in both the quality and quantity of meat and egg production. Computer-aided diagnosis has been developed to automatically identify avian malaria infections and classify the blood...