Search
310 articles for “early detection”
-
Comparative Evaluation of GPBB and CK-MB in Early Diagnosis of Acute Myocardial Infarction in Diabetic and Non-Diabetic Patients
Abstract: Background: Acute myocardial infarction (AMI) continues to be a leading cause of morbidity and death among people worldwide. To lower the risk of problems, early and precise diagnosis is essential, particularly for diabetes patients. The study investigates the diagnostic value of Glycogen Phosphorylase BB (GPBB), a potential early biomarker of myocardial necrosis, and compares it with CK-MB, a widely used cardiac marker, in AMI diagnosis. Inflammatory markers (hs-CRP, IL-6, TNF-α) …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 33–37 Read article
-
Drug Induced Immune Mediated Nephritis: Molecular Mechanism , Pathways and Clinical Implications
Abstract: Drug-induced immune-mediated nephritis (DI-IMN) has become a more widely known cause of acute kidney injury (AKI), with the potential for development to chronic kidney disease if not detected and treated promptly. T-cell hypersensitivity to pharmaceuticals, such as antibiotics, proton pump inhibitors, nonsteroidal anti-inflammatory drugs, and immunological drugs, are the major causes for it. Beyond clinical burden, DI-IMN reflectsintricate molecular interactions that sustain interstitial inflammation and tubular injury. These interactions include …
Published in International Journal of Toxins and Toxics · Vol. 3, Issue 1, 2026 · pp. 13–29 Read article
-
Essential Self-Breast Examination for Both Men and Women
Abstract: Breast self-examination stands as a crucial and foundational technique for the early detection of irregularities within the breast tissue, including both the breast itself and the nipple. This method is accessible and relevant to individuals of all genders, involving fundamental principles of observation and palpation. Those well-versed in breast self-examination possess the knowledge to guide others in this practice, which can lead to early intervention and, ultimately, the prevention of …
Published in International Journal of Midwifery Nursing And Practices · Vol. 1, Issue 2, 2023 · pp. 19–23 Read article
-
An Efficient CNN Model for Automated Cotton Leaf
Abstract: Timely and accurate identification of cotton leaf diseases are essential for maintaining healthy crop production and minimizing agricultural losses. Early detection allows farmers to take preventive or corrective measures, reducing the risk of disease spread and improving overall yield. In this study, we propose a Convolutional Neural Network (CNN) based model for the automated classification of cotton leaf diseases using image-based detection techniques. The model is trained on a diverse …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 3, 2025 · pp. 01–10 Read article
-
A Combined ECG and PPG Signal Powered Artificial Intelligence-Based Prediction Model for Stroke
Abstract: Stroke is one of the most common causes of morbidity and mortality around the world, and emphasis on prevention and early detection strategies cannot be overstated. This review aims to integrate techniques of artificial intelligence with electrocardiogram and photoplethysmogram signals to enhance stroke prediction and monitoring of cardiovascular health. All in all, the application of artificial intelligence that incorporates machine learning, deep learning, or hybrid models gives robust tools toward …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 18–26 Read article
-
Knowledge, Awareness, and Perceptions of Cervical Cancer and Screening Among Women in Rural South India
Abstract: Background: Cervical cancer is still a major public health problem in South India, with rising figures of morbidity and mortality, in spite of progress in prevention, early detection, and treatment. Cervical cancer is the second leading cause of death due to cancer among Indian women, with around 123000 new cases and 67000 deaths every year. The delay in diagnosing CVD and low participation in screening programs is due to poor …
Published in International Journal of Oncological Nursing and Practices · Vol. 3, Issue 2, 2025 · pp. 1–8 Read article
-
Data to Diagnosis: A Systematic Review of AI/ML in Healthcare
Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are fast revolutionizing the diagnosis of healthcare by augmenting accuracy, speed, and efficiency. AI/ML technologies facilitate earlier and more accurate disease identification with advanced algorithms for image processing, predictive modelling, and pattern recognition, frequently outperforming conventional diagnostic techniques. This review delves into the key contribution of AI/ML in contemporary healthcare, such as its use in clinical data analysis, imaging reports, and patient histories …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 2, 2025 Read article
-
Real-Time Browser-Based Early Warning System for Cyberbullying Detection in Online Platforms
Abstract: The rise in social networking through internet-based communication tools, Instagram, and YouTube, to name a few, significantly increases the risk of cyberbullying, thereby increasing psychological trauma on users, especially children, through adverse emotional states like anxiety, depression, etc. For a long time, researchers have been enhancing detection tools to counter cyberbullying, but their ability to detect only after the fact, along with limited support for English-based architecture, is a major …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 09–15 Read article
-
Advancements in AI-Driven Diagnostics for Dental Health: A Comprehensive Review
Abstract: Dental diseases, also known as oral diseases or dental conditions, encompass a range of health problems affecting the teeth, gums, mouth, and associated structures. These conditions can lead to pain, discomfort, and severe complications if left untreated. Early detection and accurate diagnosis are crucial for effective treatment and prevention of further complications. This comprehensive literature review aims to identify common dental problems such as Tooth Decay (Cavities), Gingivitis, Periodontitis, and …
Published in Current Trends in Signal Processing · Vol. 14, Issue 2, 2024 · pp. 1–7 Read article
-
Cervical Cancer: Understanding Its Causes, Risk Factors, and Preventive Measures
Abstract: Cervical cancer is a form of cancer that begins in the cervix, the lower portion of the uterus, due to abnormal cell growth that can spread or invade other areas of the body. In its early stages, cervical cancer usually shows no obvious symptoms, which is why regular screenings are essential for detecting it early. As the cancer advances, symptoms such as pelvic pain, unusual vaginal bleeding, and pain during …
Published in International Journal of Oncological Nursing and Practices · Vol. 3, Issue 1, 2025 · pp. 26–30 Read article
-
Earthquake Detection and Monitoring System
Abstract: Earthquakes continue to be one of the major natural hazards affecting human life and infrastructure. The development of affordable monitoring systems is essential for increasing preparedness and reducing the impact of such disasters. This work presents an Earthquake Detection and Monitoring System based on a vibration sensor and Arduino controller. The system continuously observes ground movements and evaluates the detected vibration levels against a predefined threshold. Whenever unusual vibrations are …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 2, 2026 Read article
-
Skin Disease prediction and classification from dermoscopy images using Neural Network
Abstract: Skin diseases are among the most common health-related problems affecting people of all age groups, and their occurrence often varies with seasonal and environmental conditions. Delayed or incorrect diagnosis of skin disorders can lead to severe complications, making early and accurate detection extremely important for effective treatment and prevention. In recent years, rapid advancements in deep learning and neural network technologies have significantly contributed to the development of automated medical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
-
Assessment of Women's Knowledge of Mastitis at Indus International Hospital, Punjab
Abstract: Mastitis is a non-cancerous inflammatory condition of the breast, often resulting from infection, which can impact the mammary gland's structures. It is a relatively frequent condition, affecting between 5% and 33% of women during lactation at some point in their lives. Typical clinical signs include pain in one breast, redness (erythema), and swelling, often accompanied by flu-like symptoms such as fever, chills, and body aches. Upon examination, the affected breast …
Published in Research and Reviews: A Journal of Health Professions · Vol. 14, Issue 3, 2024 Read article
-
Early Lung Cancer Prediction using deep Learning
Abstract: Lung cancer is a global killer because it’s often found late. Finding it early is key to treatment and survival so computer assisted diagnostics are essential. This research uses deep learning to spot early stage lung cancer from CT scans. We trained and fine-tuned three convolutional neural networks—ResNet50, Dense Net 201 and EfficientNet-B0—using transfer learning. We preprocessed the lung CT images by resizing, normalizing and augmenting them to enhance the …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 Read article
-
Nanoparticle-Based Early Diagnostic Tools for Tuberculosis and Malaria in Rural India
Abstract: Malaria and Tuberculosis continue to be two major public health challenges in rural India. The interplay between an inefficient health care system, late diagnosis, and under-identification of cases contributes to the high morbidity and mortality associated with TB and Malaria. Conventional methods, such as sputum microscopy for TB, microscopy and rapid diagnostic tests (RDTs) for malaria, have a higher benchmark of sensitivity that requires a certain amount of time, skilled …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 45–51 Read article
-
Non-Small Cell Lung Cancer: Types, Pathogenesis, Diagnosis, and Novel Therapeutic Strategies
Abstract: Non-small cell lung cancer (NSCLC) is the most prevalent type of lung cancer, accounting for over 85% of all cases globally. It remains one of the primary causes of cancer-related death due to its rapid progression, few early symptoms, and late detection. The three main forms of non-small cell lung cancer (NSCLC) are adenocarcinoma, squamous cell carcinoma, and giant cell carcinoma; each has a unique histology, prognosis, and response to …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 2, 2026 Read article
-
Nanotechnology-Enhanced Wearable Biosensors for Liver Disease Detection: Integration with AI for Predictive Analytics
Abstract: The worldwide health burden of liver diseases is substantial, and effective treatment and management depend heavily on early detection. This study investigates the integration of nanotechnology-enhanced wearable biosensors with artificial intelligence (AI) techniques for predictive analytics in liver disease detection. The construction of extremely selective and sensitive biosensors that can identify a variety of biomarkers linked to liver illnesses has been made possible via nanotechnology. These nanotechnology-based biosensors can be …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 14, Issue 1, 2024 · pp. 22–36 Read article
-
Breast Cancer and Enhancement through Multimedia Instruction
Abstract: The health belief model served as the foundation for the study to determine the factors that most affect women's decisions to receive a breast cancer screening that examined how study participants changed after receiving a multimedia health education intervention. After that, we could create a plan to advance women's rights for the upcoming breast cancer mammograms. Following the multimedia health education intervention, the experimental group demonstrated significantly higher scores in …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 1, 2025 · pp. 35–39 Read article
-
A Split and Merge UNet: A Deep Learning Assisted UNet Model to Segment Corpus Callosum of Brain for Automatic Autism Detection
Abstract: In recent years, deep learning techniques have shown remarkable performance in various image analysis applications, particularly in the domain of medical image processing. Among these, image segmentation plays a critical role, as it helps in isolating and analyzing specific regions within medical images. The proposed study focuses on segmenting the corpus callosum, a vital structure in the human brain, using a novel optimization technique known as the Split and Merge …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
-
Plant Disease Detection Using Machine Learning
Abstract: Plant diseases significantly threaten global crop yields and affect both nutritional safety and farmer income. Accurate and early detection of plant diseases is essential for effective intervention and treatment. In this study, we used the CNN model (convolutional neural network) to explore a deep learning-based approach for plant disease classification. The model was trained and evaluated on a large dataset encompassing 38 different classes of plant disease, including healthy leaves. …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 2, 2025 · pp. 07–19 Read article