Search
310 articles for “early detection”
-
Hybrid Techniques in Mango Leaf Disease Identification: Evaluating Neural Networks and Support Vector Machines
Abstract: Mango leaf diseases pose a significant threat to mango production, impacting both yield and fruit quality. Early and accurate detection of these diseases is crucial for effective management. This paper evaluates the use of hybrid techniques, specifically the integration of neural networks (NNs) and support vector machines (SVM), in the identification and classification of mango leaf diseases. NN excel in extracting complex features from images, while SVMs are robust classifiers, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 19–27 Read article
-
Non -Invasive Ways to Detect Cancer
Abstract: Cancer is a diverse group of diseases characterized by uncontrolled cell growth and division, affecting millions worldwide and being a leading cause of death. The disease typically involves genetic alterations that disrupt the normal balance of cell growth, leading to the formation of tumors. Tumors can be benign, posing no threat as they do not spread, or malignant, capable of invading nearby tissues and metastasizing. There are more than 100 …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 2, 2024 · pp. 59–67 Read article
-
A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression
Abstract: Early diagnosis of genetic diseases is crucial for effective treatment, especially in the case of Leukemia, a type of blood cancer characterized by abnormal proliferation of white blood cells. This paper presents a systematic review of recent computational techniques for the detection and classification of Leukemia using gene expression data obtained from DNA microarray analysis. The study explores diverse methodologies including machine learning (ML), deep learning (DL), and bio-inspired algorithms …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 Read article
-
Investigation of Electronic Transport Characteristics of Co-Doped B40 Molecular Junction for Detection of Isoprene: A DFT Study
Abstract: The early identification of lung cancer is crucial and it can be diagnosed non-invasively by assessing the exhalation. Analysing a patient's breath profile can reveal malignant growths in their lungs. In this work, B40 co-doped with indium and iron is used as a molecular junction to sense isoprene, a well-known lung cancer biomarker present in the exhalation. The electronic transport characteristics of the molecular junction designed for isoprene detection are …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 907–916 Read article
-
Milk Allergy: Significance, Detection and Management
Abstract: Milk allergy is a significant public health issue, particularly among infants and young children, with prevalence rates between 2 and 6% in early childhood, declining to 0.1–0.5% in adulthood. It is an immune-mediated adverse reaction to milk proteins, primarily involving immunoglobulin E (IgE)-mediated responses. Symptoms range from gastrointestinal distress and respiratory complications to severe anaphylaxis. The etiology of milk allergy involves genetic predisposition, environmental factors, an immature immune system, and …
Published in Research and Reviews : Journal of Dairy Science and Technology · Vol. 14, Issue 1, 2025 · pp. 15–19 Read article
-
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
-
Heart Attack Prediction Using Machine Learning
Abstract: Heart attacks have become a prevalent and serious condition in recent years due to a variety of causes. Numerous variables, including age, sex, fat, and others, can be used to predict it. In the current study, it was found that a data set with 13 parameters and 302 distinct data values, collected from a Kaggle dataset to assess patient condition, was covered. This article delves into the application of machine …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
-
X-ray Telescopes: Technological Developments and Contributions to High-Energy Astrophysics
Abstract: X-ray telescopes have revolutionized our understanding of the high-energy universe, unveiling phenomena that are invisible to optical telescopes. This paper reviews the technological advancements in X-ray telescope design, instrumentation, and data analysis techniques, which have significantly enhanced their sensitivity and resolution. We trace the development from early X-ray detectors to modern space-based observatories like the Chandra X-ray Observatory and the XMM-Newton. These advancements have facilitated groundbreaking discoveries, such as the …
Published in International Journal of Universe · Vol. 1, Issue 1, 2025 Read article
-
Need of a Comprehensive and Feasible Psychometric Test in the Assessment of Perinatal Mental Health - A Systematic Review
Abstract: The perinatal period is a period of happiness as well as hardships. A woman undergoes many psychological changes during this period which makes her prone to mental health disorders that can be detrimental to the health of the women and her child. Its essential to detect these disorders as early as possible and hence a psychometric test or tool which is easy to administer and interpret is needed. Globally various …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 104–111 Read article
-
A Thorough Examination of How Artificial Intelligence is Affecting the Transformation of Agriculture in India and Throughout the World
Abstract: By providing creative ways to increase crop yields, maximize resource usage, and advance sustainability, artificial intelligence (AI) is revolutionizing agriculture. AI technologies, such as machine learning, computer vision, and robotics, are being increasingly used in precision farming, crop monitoring, disease detection, and decision-making as the global agricultural sector faces pressing challenges like food security, population growth, and climate change. AI enables farmers to make data-driven decisions, optimize irrigation systems, monitor …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 39–45 Read article
-
Comparative Analysis and Future Research Directions in AI in Healthcare: Medical Imaging and Diagnostics
Abstract: Artificial intelligence (AI) is reshaping healthcare, particularly in the areas of medical imaging and diagnostic practice. By using advanced techniques like machine learning and deep learning, AI systems help improve the accuracy, speed, and effectiveness of identifying diseases and analyzing medical images. This paper provides a comprehensive overview of the application of artificial intelligence in medical imaging and highlights its growing importance in clinical diagnostics. It discusses how AI-based systems …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 8–13 Read article
-
A Hybrid Mathematical Model for Epidemic Outbreak Forecasting Using Machine Learning and Cloud Computing
Abstract: The increasing frequency of infectious disease outbreaks has emphasized the necessity for intelligent epidemic surveillance systems capable of predicting disease spread at an early stage. Conventional outbreak detection approaches rely heavily on delayed statistical reporting and manual monitoring techniques, resulting in reduced responsiveness during critical periods. This paper presents a mathematical predictive framework for epidemic outbreak detection using machine learning and cloud computing technologies. The proposed framework integrates the Susceptible–Infected–Recovered …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 01–06 Read article
-
Lemon Sign: The Diagnostic Indicator for Spina Bifida
Abstract: The “lemon sign” is a distinctive ultrasonographic finding that serves as a diagnostic indicator for spina bifida, a congenital neural tube defect characterized by incomplete closure of the spinal cord. This sign is observed in fetal imaging and is considered an early and reliable marker for detecting spina bifida, particularly when combined with other prenatal diagnostic tools such as the “banana sign.” The lemon sign is characterized by a flattened, …
Published in International Journal of Midwifery Nursing And Practices · Vol. 4, Issue 1, 2026 · pp. 1–6 Read article
-
IoT-Based Structural Health Monitoring and Damage Detection in Fiber Reinforced Polymer Composite Structures
Abstract: Applications of fiber-reinforced polymer (FRP) composite in the aerospace, civil infrastructure and renewable energy systems are increasing due to the fact that the composite possesses high ratio of strength to weight and can resist corrosion. However, processes of internal damages such as the cracking of the matrix, delamination and fiber fracture, are likely to take place without being visible on the surface and therefore a periodic check of the structure …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1076–1100 Read article
-
Study on Brain Tumor Detection Using Morphological Operations in MATLAB with Graphical User Interface (GUI)
Abstract: Brain tumor detection plays a crucial role in early diagnosis and effective treatment planning. This research presents a MATLAB-based Graphical User Interface (GUI) for Brain Tumor Detection, incorporating a comprehensive pipeline of image processing techniques. The GUI provides a user-friendly platform, empowering medical professionals to accurately and efficiently analyze MRI brain scans. The GUI begins with text removal to eliminate any textual artifacts that may be present in the MRI …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 24–31 Read article
-
IoT and Smart Sensors for Structural Health Monitoring: Trends, Challenges, and Future Directions
Abstract: Structural Health Monitoring (SHM) plays a critical role in ensuring the safety, resilience, and sustainability of civil infrastructure systems. In recent years, the convergence of Internet of Things (IoT) technologies and smart sensor systems has revolutionized the field of SHM. This integration enables continuous, real- time monitoring, facilitates predictive maintenance, and reduces the costs associated with structural inspections. IoT-based SHM frameworks leverage wireless sensor networks, cloud computing platforms, and intelligent …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 3, 2025 · pp. 1–6 Read article
-
A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
-
From Battlefield to Biodiversity: The Evolution of Drones in Modern Conservation Efforts in Wildlife
Abstract: The rapid advancement of drone technology, encompassing unmanned aerial vehicles (UAVs), unmanned aircraft systems (UAS), and remotely piloted aircraft (RPAs), has significantly impacted various fields, particularly environmental management and wildlife conservation. Originally designed for military use, drones have now become essential tools in ecological research, offering a cost-effective and minimally invasive way to monitor and protect ecosystems. These sophisticated "eco-drones" have revolutionized data collection, especially in hard-to-reach and previously inaccessible …
Published in International Journal on Drones · Vol. 1, Issue 1, 2025 · pp. 8–12 Read article
-
Innovations in Tuberculosis Management: Advancements in Drug-Resistant TB Treatment and Rapid Diagnostics
Abstract: Tuberculosis (TB) remains one of the deadliest infectious diseases worldwide, exacerbated by the increasing prevalence of drug-resistant strains, such as multidrug-resistant (MDR-TB) and extensively drug-resistant TB (XDR-TB). Despite advancements in first-line and second-line treatments, resistance to conventional antibiotics has complicated therapeutic strategies, necessitating novel approaches. This mini review explores emerging advancements in TB treatment, including gene editing technologies, such as CRISPR, which offer potential for precise targeting of drug-resistant bacterial …
Published in International Journal of Antibiotics · Vol. 2, Issue 2, 2025 · pp. 1–7 Read article
-
A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 Read article