Intelligent image-based colourimetric tests using machine learning framework for lateral flow assays

This paper aims to deliberately examine the scope of an intelligent colourimetric test that fulfils ASSURED criteria (Affordable, Sensitive, Specific, User-friendly, Rapid and robust, Equipment-free, and Deliverable) and demonstrate the claim as well. This paper presents an investigation into an intelligent image-based system to perform automatic paper-based colourimetric tests in real-time to provide a proof-of-concept for a dry-chemical based or microfluidic, stable and semi-quantitative assay using a larger dataset with diverse conditions. The universal pH indicator papers were utilised as a case study. Unlike the works done in the literature, this work performs multiclass colourimetric tests using histogram based image processing and machine learning algorithm without any user intervention. The proposed image processing framework is based on colour channel separation, global thresholding, morphological operation and object detection. We have also deployed a server based convolutional neural network framework for image classification using inductive transfer learning on a mobile platform. The results obtained by both traditional machine learning and pre-trained model-based deep learning were critically analysed with the set evaluation criteria (ASSURED criteria). The features were optimised using univariate analysis and exploratory data analysis to improve the performance. The image processing algorithm showed >98% accuracy while the classification accuracy by Least Squares Support Vector Machine (LS- SVM) was 100%. On the other hand, the deep learning technique provided >86% accuracy, which could be further improved with a large amount of data. The k-fold cross validated LS- SVM based final system, examined on different datasets, confirmed the robustness and reliability of the presented approach, which was further validated using statistical analysis. The understaffed and resource limited healthcare system can benefit from such an easy-to-use technology to support remote aid workers, assist in elderly care and promote personalised healthcare by eliminating the subjectivity of interpretation

Assay Type Detection Using Advanced Machine Learning Algorithms

The colourimetric analysis has been used in diversified fields for years. This paper provides a unique overview of colourimetric tests from the perspective of computer vision by describing different aspects of a colourimetric test in the context of image processing, followed by an investigation into the development of a colorimetric assay type detection system using advanced machine learning algorithms. To the best of our knowledge, this is the first attempt to define colourimetric assay types from the eyes of a machine and perform any colorimetric test using deep learning. This investigation utilizes the state-of-the-art pre-trained models of Convolutional Neural Network (CNN) to perform the assay type detection of an enzyme-linked immunosorbent assay (ELISA) and lateral flow assay (LFA). The ELISA dataset contains images of both positive and negative samples, prepared for the plasmonic ELISA based TB-antigen specific antibody detection. The LFA dataset contains images of the universal pH indicator paper of eight pH levels. It is noted that the pre-trained models offered 100% accurate visual recognition for the assay type detection. Such detection can assist novice users to initiate a colorimetric test using his/her personal digital devices. The assay type detection can also aid in calibrating an image-based colorimetric classification

Rancang Bangun Aplikasi Android Untuk Mengukur Konsentrasi Leukosit Esterase Dan Keberadaan Nitrit Dalam Urin Pada Hasil Tes Dipstick Untuk Studi Kasus Infeksi Saluran Kemih

Dilema utama dalam dunia medis adalah dalam pemberian obat-obatan untuk pasien asimtomatik yang terdeteksi bakteri pada urinnya . Penggunaan obat antibiotik dalam beberapa kasus dapat menyembuhkan penyakit infeksi saluran kemih yang terdeteksi dini. Namun, karena bakteri akan membentuk sistem imun terhadap obat, penting untuk tidak melakukan pemberian obat antibiotik pada pasien asimtomatik kecuali terdapat bukti kuat bahwa pasien terdeteksi penyakit infeksi saluran kemih. Namun mengingat instrumen yang sudah ada berharga relatif mahal dan hanya dapat digunakan oleh tenaga ahli, penggunaan kamera smartphone dapat digunakan dalam pembacaan warna reagen dipstick urinalysis sebagai salah satu instrumen untuk pendeteksian bakteri pada urin sejak dini. Untuk mencapai tujuan tersebut diperlukan sebuah sistem pengolahan warna reagen pada dipstick yang dapat dipasang pada smartphone, khususnya untuk reagen leukosit esterase dan nitrit yang merupakan indikator untuk menentukan kemunculan bakteri pada urin. Salah satu permasalahan dalam sistem tersebut adalah menentukan metode dan ruang warna yang sesuai, sehingga nilai warna yang didapat dapat merepresentasikan warna yang dapat diolah menjadi hasil yang viii akurat dan dapat dipercaya. Sistem yang dapat memperoleh nilai yang dapat merepresentasikan warna yang ada dalam citra strip dipstick dikembangkan dalam ruang warna CIELab dengan menerapkan metode berbasis Stepwise Linear Interpolation untuk mengukur tingkat konsentrasi leukosit esterase dan nitrit. Hasil uji coba menunjukkan bahwa metode Stepwise Linear Interpolation dapat digunakan untuk mengidentifikasikan level reagen leukosit dan nitrit. Namun, kalibrasi hitam putih belum dapat diterapkan sebagai representasi kalibrasi pencahayaan karena memiliki tingkat akurasi yang rendah sehingga penggunaan data master masih belum dapat dilakukan. Selain itu dalam beberapa kasus reagen leukosit membutuhkan penelitian lebih lanjut untuk menghasilkan metode yang sesuai dalam mengidentifikasikan warna yang tidak sesuai dengan level warna. ========================================================================================================= A common dilemma in clinical medicine is whether to treat asymptomatic patients who present with bacteria in their urine. There are few scenarios in which antibiotic treatment of asymptomatic bacteriuria has been shown to improve patient outcomes. Because of increasing antimicrobial resistance, it is important not to treat patients with asymptomatic bacteriuria unless there is evidence of potential benefit. For this purpose, a urinalysis dipstick reagent color acquisition is important, mainly for leukocytes esterase and nitrites reagent which can be an indicator for early detection of Urinary Tract Infection (UTI). Smartphone camera can be used to help people interpreting reagent colors, rather than using expensive instrument that can only be used by professionals. To accomplish that goal a system that can interpret reagent colors and can be installed on smartphone is needed. One of the main issue in developing this system is what color space and method are used, so the values extracted can represent color in the dipstick for further process to obtain reliable result . Reagent detection and acquisition system is developed CIELab color space using a Stepwise Linear Interpolation based method to measure the level of leukocytes esterase and nitrites reagent in urine. x Experimental result proves that Stepwise Linear Interpolation can determine reagent level of nitrite and leukocytes. But, black white calibration can’t representing light calibration so data master can’t be applied. And in some situation, a further experiment needed for produce reliable method that can determine reagent level which are not in color chart

A review on urinary tract infections diagnostic methods: Laboratory-based and point-of-care approaches

Urinary tract infections (UTIs) are among the most common infectious diseases worldwide. This type of infections can be healthcare-associated or community-acquired and affects millions of people every year. Different diagnostic procedures are available to detect pathogens in urine and they can be divided into two main categories: laboratory-based and point-of-care (POC) detection techniques. Traditional methodologies are often timeconsuming, thus, achieving a rapid and accurate identification of pathogens is a challenging feature that has been pursued by many research groups and companies operating in this area. The purpose of this review is to compare and highlight advantages and disadvantages of the traditional and currently most used detection methods, as well as the emerging POC approaches and the relevant advances in on-site detection of pathogens ' mechanisms, suitable to be adapted to UTI diagnosis. Lately, the commercially available UTI self-testing kits and devices are helping in the diagnosis of urinary infections as patients or care givers are able to perform the test, easily and comfortably at home and, upon the result, decide when to attend an appointment/Urgent Health Care Unit.info:eu-repo/semantics/publishedVersio

Aplicativos móviles para el diagnóstico y prevención de la ictericia usando uroanálisis con tiras reactivas determinando urobilinógeno en Lima Metropolitana 2021

La ictericia es un problema mayor en el mundo, y se busca prevenir y/o diagnosticarlo a tiempo. Objetivo: Determinar si los aplicativos móviles serán eficaces para la prevención de la Ictericia y optimizarán el trabajo de laboratorio clínico. Metodología: el objetivo específico-2 consiste en aplicación de una encuesta a técnicos laboratoristas clínicos, población-243 Y muestra-56, con la aplicación de 6 ítems evaluándose con estadístico F para la prueba de hipótesis. Además, se realizó búsqueda en google escolar para los objetivos específicos 1y3, se utilizó el análisis temático, tabulándose 1,175,616 artículos con palabras en todo el articulo y 91,955 artículos con palabras solo en el titulo expresando los resultados a semejanza de un meta-análisis cualitativo. Resultados: 58.9% están algo de acuerdo y muy de acuerdo que los aplicativos móviles optimicen el trabajo de laboratorio clínico. en urianalysis Entre 1981- 1985 se incrementó exponencialmente respecto en todo-el artículo, para Mobile Phone y Smartphone A partir de 1995 empieza a ver información para ambas palabras, en urobilinogen hay incremento en el titulo entre 1946 a 1950 y en 1956 a 1960, Se produce un ascenso solo en el titulo para Reagent Strips desde 1976 a 1990, la Ictericia, en todo el artículo en el año 2006 a 2010 es donde alcanza el pico más alto de información. Conclusiones: Las apps-móviles son muy útiles-para-analizar urobilinógeno, las apps-móviles optimizarán el trabajo en laboratorios, No-hay un examen directo para prevenir la ictericia, el análisis de urobilinógeno en orina sirve como un examen complementario para su diagnóstico y/o prevenciónhttp://repositorio.unid.edu.pe/handle/unid/197?show=ful

Photonic Hydrogel Sensors

Analyte-sensitive hydrogels that incorporate optical structures have emerged as sensing platforms for point-of-care diagnostics. The optical properties of the hydrogel sensors can be rationally designed and fabricated through self-assembly, microfabrication or laser writing. The advantages of photonic hydrogel sensors over conventional assay formats include label-free, quantitative, reusable, and continuous measurement capability that can be integrated with equipment-free text or image display. This Review explains the operation principles of photonic hydrogel sensors, presents syntheses of stimuli-responsive polymers, and provides an overview of qualitative and quantitative readout technologies. Applications in clinical samples are discussed, and potential future directions are identified

Photonic hydrogel sensors

Analyte-sensitive hydrogels that incorporate optical structures have emerged as sensing platforms for point-of-care diagnostics. The optical properties of the hydrogel sensors can be rationally designed and fabricated through self-assembly, microfabrication or laser writing. The advantages of photonic hydrogel sensors over conventional assay formats include label-free, quantitative, reusable, and continuous measurement capability that can be integrated with equipment-free text or image display. This Review explains the operation principles of photonic hydrogel sensors, presents syntheses of stimuli-responsive polymers, and provides an overview of qualitative and quantitative readout technologies. Applications in clinical samples are discussed, and potential future directions are identified