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137 articles for “severity classification”
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Comparison between two severity classificaitons in patients with acute cholecystitis
Abstract: Background and objective: Assessment severity helps clinicians to guide appropriate treatment and minimumize adverse outcome. The objective of our study was to comparison between TG13 severity system and EGS grade system for predicting clinical outcomes in acute cholecystitis. Patients and method: This is a retrospective single-center study which enrolled patients who were admitted to pyongsong medical university hospital between February 2020 and October 2021. Tokyo 2013(TG 13) severity classification and …
Published in Research and Reviews : Journal of Surgery · Vol. 12, Issue 2, 2023 Read article
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Clinical Classification of Knee OA Severity Using WOMAC and its Association with Fear of Falling and Functional Capacity
Abstract: Aim: To determine whether clinically classifying knee osteoarthritis (OA) using the Western Ontario and McMaster Universities Arthritis Index (WOMAC) is as effective as radiological classification. Methodology: A total of 36 subjects with diagnosed knee OA who visited the physiotherapy OPD of ESI Hospital, Basaidarapur, New Delhi, India, were included in the present study. Procedure: Subjects were screened for cognitive ability using Mini-Mental State Exam (MMSE), fear of falling using Modified …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 8, Issue 3, 2019 · pp. 32–38 Read article
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Crop Yield Prediction Using Machine Learning Algorithm Based on Climate Variables
Abstract: India's economy is based primarily on agriculture, as over 50% of the country's population depends on it for their livelihood. The long-term viability of agriculture is seriously threatened by variations in the weather, climate, and other environmental factors. Because machine learning provides tools for decision assistance in agricultural yield prediction, including guidance on which crops to plant and when to plant them during the growing season, it is essential to …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 49–52 Read article
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Timestamp Extraction and Log Classification Using Supervised Machine Learning: A Comparative Study
Abstract: In modern software systems, logs are vital for monitoring application behavior, diagnosing issues, and analyzing performance. Timestamps are especially important for sequencing events, identifying anomalies, and understanding system failures. However, detecting timestamps in logs is challenging due to inconsistent formatting across systems and the presence of timestamp-like strings in non-timestamp fields. Traditional rule-based methods often fail in such cases. This study proposes a supervised machine learning approach to accurately classify …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 26–38 Read article
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IoT-Based Emergency SOS System for Post-Accident Assistance
Abstract: The increase in road accidents poses significant challenges for timely medical response, often leading to life-threatening delays. This project proposes an IoT-based accident wound detection system that utilizes a night vision camera mounted on either the interior or exterior of a vehicle. The system aims to detect injuries sustained by individuals during a collision and promptly alert emergency services. By employing a night vision camera, the system can operate effectively …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 2, 2025 · pp. 11–19 Read article
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A Review of Automated Pomegranate Disease Detection and Classification Using Machine Learning
Abstract: The abstract outlines a research study focused on developing an automated system for detecting and classifying diseases that affect pomegranate fruits. Pomegranates, like many other crops, are vulnerable to several types of diseases that appear as visible colored spots on the fruit’s surface. These visible symptoms, such as lesions or discoloration, can significantly impact the fruit’s quality, market value, and yield. Therefore, timely and accurate identification of such diseases is …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 01–13 Read article
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Crop Disease Prediction by Machine Learning
Abstract: The classification of Crop can be classified into several methods. The data set of crop leaf illnesses, notably Bacterial Leaf Blight disease (BLB), a crop leaf disease with significant outbreaks throughout Thailand, and Brown Spot Crop disease (BSR), is classified employing image classification in this study. Additionally, image processing technology is used for identifying different types of crop leaf disease. These algorithms include the Random Forest, Decision Tree, Gradient Boost, …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 21–25 Read article
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Microneedles: A Modern Breakthrough in Drug Delivery Systems
Abstract: Microneedles (MNs) represent a revolutionary and transformative advancement in the realm of transdermal drug delivery systems, which are designed to facilitate the administration of therapeutic agents through the skin. These exceptionally small, micron-scale needles penetrate the stratum corneum, thereby enabling the direct delivery of pharmacological agents into the underlying dermis or the upper epidermis, consequently enhancing bioavailability while simultaneously circumventing the detrimental effects of first-pass metabolism and the degradation that …
Published in Trends in Drug Delivery · Vol. 12, Issue 3, 2025 · pp. 01–07 Read article
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Distancing From Statistical Hazards: A Pursuit Drivers Herald
Abstract: When the passive drivers meet with accidents, it seems painful. When miscreant drivers cause accidents one feels annoyed, and curses the nasty driver and also the system. Statistics promises help in at least one way- i.e. keeping the safe distance between the two vehicles. Statistically speaking, frequency/ probability of happening of accidents is inversely proportional to the distance. The distance forms a bell shape in normal stopping situations on the …
Published in Journal of Production Research & Management · Vol. 2, Issue 1-2-3, 2012 · pp. 37–49 Read article
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Image Processing Techniques for Detecting and Classification of Leaf Diseases
Abstract: Plants are the way to make a living. From the factors of our daily life to breathing we are totally dependent on plants. Therefore, plant care must be proper. Plant diseases involve, of instance, algae, bacteria, and viruses. Several researchers have to classify plant diseases but it is time consuming to manually identify them. Image processing techniques are used to detect various diseases of the plant. There are several steps …
Published in Trends in Opto-electro & Optical Communication · Vol. 11, Issue 2, 2021 · pp. 1–6 Read article
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A Method to Produce a GIS Database of Asphalt Polymer Pavement Distress of National Highway
Abstract: Bitumen, often referred to as asphalt in its solid form, is a complex mixture of organic compounds derived from the distillation of crude oil. Its chemical composition varies depending on its source, processing methods, and intended application. Pavement surface monitoring is an important part to increase the life of pavement and to minimize the cost incur in maintenance of pavement at an early stage. Traditionally pavement monitoring done using manually …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 99–108 Read article
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Characterization of Cellulose Producing Bacterial Isolates from Rotten Fruits
Abstract: Cellulose, the most abundant natural polymer, is predominantly sourced from plant wood but can also be synthesized by certain bacteria in the form of bio-cellulose. The potential applications of bio-cellulose are extensive, particularly in the biomedical field for tissue engineering, drug delivery, and more. The distinct properties and purity of bacterial cellulose, in contrast to plant-derived cellulose, underscore its importance and drive further research in the area. This study focuses …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 14, Issue 1, 2024 · pp. 38–45 Read article
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Early Heart Disease Prediction Using Hybrid Machine Learning Techniques
Abstract: In the contemporary era, cardiovascular disease is one in all the most causes of death within the world. Estimating Heart problems i.e cardiopathy is a crucial challenge within the area of clinical data analysis. Large volumes of data produced by the healthcare sector have been proved to be useful for helping with decision-making and speculation, thanks to machine learning (ML).. Various studies help us to review and supply glimpse into …
Published in Journal of Microcontroller Engineering and Applications · Vol. 9, Issue 2, 2022 · pp. 35–41 Read article
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Chronic Kidney Disease: An Overview
Abstract: The key purpose of this review article is to throw light on chronic kidney disease (CKD). Each day people are diagonised with CKD making the need of proper awareness regarding CKD, one of the top public health priorities. Taking this into consideration, the review article outlines some new insight on identification of CKD, classifying it into several stages based on glomerular filtration rate (GFR)/chronic renal failure (CRF) value to be …
Published in Research and Reviews: A Journal of Medicine · Vol. 8, Issue 1, 2018 · pp. 6–9 Read article
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Integration of Multispectral Satellite data with Ensemble Machine Learning Models for Wetland Classification: a new Ramsar Site in Central India
Abstract: For biodiversity conservation, several wetlands in India have been classified as Ramsar sites, and Sirpur Lake is a recent addition to the list. The objective of this paper is to use Sentinel optical data with 10-meter resolution to prepare a robust and accurate classified map which will be crucial for further analysis. The data on thirteen spectral bands along with four essential spectral indices, Normalized Difference Vegetation Index (NDVI), Normalized …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 Read article
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Breast Cancer Detection and Multiple Classification Using CNN
Abstract: Although some efforts have been made in the form of preventative screening programs, breast cancer remains one of the rising causes of death in women. Computer-assisted diagnosis is needed because of the rapidly increasing number of mammograms that can be collected by these programs. Performance metrics are not significantly improved by computer aided detection methods designed to improve diagnosis without a large number of sequential readings. In this context, self-imaging …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 12, Issue 2, 2023 · pp. 28–38 Read article
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Methods Based on Machine Learning for Large-scale Classification of Crop Leaf Diseases
Abstract: Worldwide productivity of crops is seriously threatened by crop leaf diseases, which can result in large crop losses and negative economic effects. Effective disease management and crop protection depend on the early and precise detection and classification of these illnesses. Machine learning approaches have gained popularity recently due to their ability to automate procedures related to illness diagnosis and classification. An overview of the several machine learning–based methods used for …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 1, 2024 · pp. 11–23 Read article
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Eye Disease Classification Using K-means Clustering Algorithm and Ensemble Classification Approach
Abstract: In this study, we present a comprehensive approach for the classification of eye diseases, specifically targeting normal, cataract, glaucoma, and diabetic retinopathy conditions. This research uses a dataset from Kaggle, which provides a wide and varied collection of retinal images to ensure good representation. The methodology encompasses advanced image processing and machine learning techniques to ensure accurate diagnosis and prediction. The preprocessing phase involves a series of image enhancement techniques …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 15–27 Read article
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Automated Plant Disease Detection and Treatment Advisor Using Artificial Intelligence
Abstract: Automated plant disease detection and treatment advisors using artificial intelligence represent a significant advancement in modern agriculture. The identification of plant leaf diseases is essential to maintaining food security and agricultural output. Machine learning models, particularly deep learning algorithms like convolutional neural networks (CNNs), are trained on labeled datasets containing images of healthy and diseased plants. These models learn to classify images into different disease categories with high accuracy. Convolutional …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 1–7 Read article
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A Case based Practical Approach for Novel Data Transformation to Enhance Accuracy of Decision Tree Ensembles
Abstract: AbstractIf we talk about any real world situation then we can see that all the situations dramatically changes as the time passes. If we say this statement in some technical form, concepts changes gradually. This situation is called as Concept Drift that is the core of any approach. Until we cannot get the accurate output for a given input parameter, the concepts will concurrently change. To overcome this situation we …
Published in Journal of Computer Technology & Applications · Vol. 5, Issue 1, 2014 · pp. 1–6 Read article