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Introduction
We are eager to explore an innovative technological approach involving deep learning models for screening or diagnosing blood microorganisms (such as protozoa) that cause zoonotic and arthropod-borne diseases. Research into medical devices utilizing deep learning aims to enhance decision-making in identifying the causes of infections, particularly in remote areas lacking expensive equipment and skilled technicians.
Current institution
Publications
Publications (36)
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...
Background and Aim: Zoonotic diseases caused by various blood parasites are important issues of public health concern, impacting both animals and humans worldwide. The traditional method of microscopic examination for the parasite diagnosis is labor-intensive, time-consuming, and prone to variability among observers, necessitating highly skilled an...
Tracheal collapse is a chronic and progressively worsening disease; the severity of clinical symptoms experienced by affected individuals depends on the degree of airway collapse. Cutting‐edge automated tools are necessary to modernize disease screening using radiographs across various veterinary settings, such as animal clinics and hospitals. This...
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...
Human parasitic infections remain one of public health concerns for 1.5 billion people worldwide including Thailand. Conventional microscopic examination is a gold standard method and often used to identify the helminth ova and filariform larvae and also protozoa cyst in stool-dependent simple smear. The benefits of traditional techniques are dimin...
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...
Both the ABO and Rhesus (Rh) blood groups play crucial roles in blood transfusion medicine. Herein, we report a simple and low-cost paper-based analytical device (PAD) for phenotyping red blood cell (RBC) antigens. Using this Rh typing format, 5 Rh antigens on RBCs can be simultaneously detected and macroscopically visualized within 12 min. The pro...
Objective:
Radiographic interpretation suffers from an ever-increasing workload in orthopedic and radiology departments. The present study applied and assessed the performance of a convolutional neural network designed to assist orthopedists and radiologists in the detection and classification of knee osteoarthritis from early to severe degrees in...
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...
Microscopic observation of mosquito species, which is the basis of morphological identification, is a time-consuming and challenging process, particularly owing to the different skills and experience of public health personnel. We present deep learning models based on the well-known you-only-look-once (YOLO) algorithm. This model can be used to sim...
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...
Background:
Countries within the Greater Mekong Sub-region (GMS) of Southeast Asia have committed to eliminating malaria by 2030. Although the malaria situation has greatly improved, malaria transmission remains at international border regions. In some areas, Plasmodium vivax has become the predominant parasite. To gain a better understanding of t...
Background:
The malaria elimination plan of the Greater Mekong Subregion (GMS) is jeopardized by the increasing number of Plasmodium vivax infections and emergence of parasite strains with reduced susceptibility to the frontline drug treatment chloroquine/primaquine. This study aimed to determine the evolution of the P. vivax multidrug resistance...
Background: Countries within the Greater Mekong Subregion (GMS) of Southeast Asia have committed to eliminating malaria by 2030. Although malaria situation has greatly improved, Plasmodium vivax remains at international border regions. Therefore, to gain a better understanding of transmission dynamics, knowledge on the evolution of P. vivax populat...
Background Countries within the Greater Mekong Sub-region (GMS) of Southeast Asia have committed to eliminating malaria by 2030. Although the malaria situation has greatly improved, malaria transmission remains at international border regions. In some areas, Plasmodium vivax has become the predominant parasite. To gain a better understanding of tra...
Background
Countries within the Greater Mekong Subregion (GMS) of Southeast Asia have committed to eliminating malaria by 2030. Although malaria situation has greatly improved, Plasmodium vivax remains at international border regions. Therefore, to gain a better understanding of transmission dynamics, knowledge on the evolution of P. vivax populati...
Background
Plasmodium vivax transmission in Thailand has been substantially reduced over the past 10 years, yet it remains highly endemic along international borders. Understanding the genetic relationship of residual parasite populations can help track the origins of the parasites that are reintroduced into malaria-free regions within the country....
Shared haplotypes based on genotyping using the 10 microsatellites (total number of haplotypes = 124).
(DOCX)
The mean number of alleles (A) and allelic richness (B) of each microsatellite in the three populations.
(DOCX)
Remaining haplotypes (% and number) by the stepwise removal approach for all three populations (A), and individual populations from Ubon Ratchathani (B), Tak (C) and Kanchanaburi (D).
(DOCX)
Primer sets for 10 microsatellite markers for the primary and semi-nested PCR.
(DOCX)
Measurements of allelic numbers and allelic richness per locus.
(TIFF)
Association between genetic and geographic distances by the Mantel Rank test.
The correlation between genetic and geographic distance were examined by the Mantel rank test in GenAlEx 6.5. Analysis was done pairwise, using isolates within and between provinces. The X-axis represents the pairwise geographic distance and the Y-axis indicates correspon...
