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66 articles for “early detection of cancer”
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Knowledge and Attitude of Women Regarding Mammogram and Other Screening Modalities for Breast Cancer in a Selected Hospital, Kottayam
Abstract: The present study was conducted at Caritas Hospital, to assess the knowledge and attitude of women (30–50 years) regarding mammogram and other screening modalities. The study aimed to evaluate women's understanding of mammograms and various breast cancer screening methods, gauge their attitudes toward mammograms and other screening options, investigate the relationship between women's knowledge and attitudes regarding these screening methods, explore any associations between knowledge and certain demographic factors, and …
Published in International Journal of Oncological Nursing and Practices · Vol. 1, Issue 2, 2023 · pp. 36–44 Read article
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Crispr Cas – Revolutionizing Modern Therapies and Beyond
Abstract: CRISPR-Cas technology has emerged as a transformative tool in modern molecular biology, revolutionizing both fundamental research and clinical applications. This RNA-guided gene-editing system enables precise and efficient genomic modifications, offering unprecedented potential for addressing genetic disorders, infectious diseases, and oncological conditions through innovative therapeutic interventions. The inherent specificity and programmability of CRISPR-Cas systems have facilitated breakthroughs in diverse fields, including precision medicine, regenerative therapies, and immuno-oncology. Beyond its therapeutic applications, …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 1, 2025 · pp. 25–38 Read article
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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
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Cancer Chronicles: An Overview of its Origins, Types, Treatment, and Prevention
Abstract: Cancer is a multifaceted illness characterized by abnormal cell growth and dissemination throughout the body. Its onset usually arises from a mix of genetic mutations and environmental factors. There exist more than 100 distinct forms of cancer, each possessing unique attributes, risk elements, and therapeutic alternatives. Cancer is a pervasive health challenge that knows no boundaries of age, race, or background, continuing to rank among the foremost causes of mortality …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 2, 2024 · pp. 36–42 Read article
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Designing and Developing a Cancer Chatbot in a Website
Abstract: Cancer is a disease that affects millions of people worldwide each year and is characterized by the rapid growth of cells that are abnormal. The outcome is affected since numerous cases are discovered at advanced stages of the disease. Anxiety and depression are two mental health issues that frequently coexist with the illness, worsening its effects on sufferers. There were many medical apps that provide guidelines for patients, but these …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 1, 2024 · pp. 1–9 Read article
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Knowledge, Attitude, and Practice Regarding Breast Cancer and Its Prevention Among Adolescent School-Going Girls
Abstract: Introduction: Breast cancer claims the lives of over 500,000 women globally each year. In low-resource settings, most women are diagnosed at an advanced stage of the disease, resulting in low 5-year survival rates, typically ranging between 10 and 40%. However, in regions where early detection and basic treatment are both available and accessible, the 5-year survival rate for early-stage localized breast cancer can exceed 80%. Objectives of the Study: The …
Published in International Journal of Community Health Nursing And Practices · Vol. 3, Issue 2, 2025 · pp. 1–9 Read article
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CNN-Based Diagnosis of Skin Cancer from Dermoscopic Images
Abstract: Skin cancer has become one of the diseases widely spread over the globe, with melanoma becoming a severe threat to one’s health. Detection of such diseases at the initial stage saves an individual from drastic damage. Using a Convolutional Neural Network (CNN) for detecting skin cancer through image classification as benign or malignant provides significant support to dermatological practice and reduces dependence solely on subjective visual examination. Dermatologists often face …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 1, 2026 · pp. 37–42 Read article
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In Silico Exploration of Podophyllum Hexandrum-Derived Phytocompounds as Potential Therapeutics Against Small Cell Lung Cancer (SCLC): A Molecular Docking Approach
Abstract: Small Cell Lung Cancer (SCLC) is a fast-growing and aggressive type of lung cancer that spreads quickly strongly associated with smoking. It is characterized by symptoms, such as persistent cough, breathing difficulties, or hoarseness, though it can sometimes be asymptomatic which makes early detection challenging. The tumor suppressor gene TP53 is critical in regulating the cell cycle and preventing uncontrolled cell division. Mutations in TP53 result in the loss of …
Published in International Journal of Molecular Biotechnological Research · Vol. 3, Issue 1, 2025 · pp. 1–11 Read article
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Comparative Study of Machine Learning Algorithms for Detection of Breast Cancer
Abstract: Breast cancer continues to be the most commonly diagnosed cancer among women, with more than 2.3 million new cases diagnosed yearly worldwide. It is stated as the leading cause of cancer-related deaths. Therefore, this emphasizes the dire necessity for early diagnosis with a view to improving survival. Early diagnosis elevates the effectiveness of prediction and treatment. This research carries out a structured and analytical evaluation of various machine learning algorithms, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 113–129 Read article
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Cancer Chemotherapy-Induced Cachexia: Bridging Mechanisms, Management, and Future Therapies
Abstract: Involuntary weight loss, skeletal muscle atrophy, adipose tissue depletion, anorexia, and systemic inflammation are all symptoms of chemotherapy-induced cachexia, a complex illness. Although it is common, it remains poorly understood and is often referred to as an "orphan disease." This study covers the epidemiology, pathophysiology, clinical symptoms, diagnosis, treatment, and emerging treatment options for chemotherapy-induced cachexia. To comprehend the causes, clinical results, and therapeutic approaches, a literature-based synthesis of recent …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 1, 2026 · pp. 17–26 Read article
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Breast Cancer Detection Using Machine Learning: A Comparative Analysis of Supervised Learning Algorithms
Abstract: Globally, breast cancer remains a predominant cause of mortality among women, highlighting the urgent need for timely and precise diagnostic approaches. This research explores the application of machine learning algorithms—including Logistic Regression, SVM, Naïve Bayes, KNN, and Random Forest—on the Wisconsin Breast Cancer Dataset for effective tumor classification. Key pre-processing steps such as missing value handling, feature scaling, and dimensionality reduction were employed to improve model performance. The study evaluated …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 46–52 Read article
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Extracellular Vesicle-Based Liquid Biopsies: Decoding the Tumor Microenvironment for Precision Oncology
Abstract: The tumor microenvironment (TME) plays a pivotal role in cancer initiation, progression, and therapeutic response. Decoding the TME is, therefore, essential for advancing precision oncology. Extracellular vesicles (EVs), including exosomes and microvesicles, are nanoscale lipid bilayer particles secreted by tumor and stromal cells. They transport a wide range of bioactive molecules, such as DNA, RNA, proteins, lipids, and metabolites, which reflect the dynamic state of the TME. Recent advances in …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 1, 2026 · pp. 43–62 Read article
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Computer Aided Diagnosis of Breast Cancer using Machine Learning Techniques
Abstract: Breast cancer is one of the significant health problems that lead to early mortality in women, especially those between 40 and 55 years of age all over the world. In recent years, the number of breast cancer cases among women has risen significantly, making early and accurate diagnosis more important than ever. Computer-aided diagnostic (CAD) tools have become valuable in supporting radiologists by enhancing the precision of breast cancer detection. …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 2, 2025 · pp. 1–11 Read article
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Cross-Domain Comparative Analysis of Microwave Imaging Systems for Medical Diagnostics and Industrial Testing
Abstract: Microwave imaging is gaining significant traction as a non-ionizing, low-cost, and portable alternative to conventional diagnostic and inspection modalities in both medical and industrial domains. Leveraging the dielectric contrast between healthy and anomalous tissues or materials, microwave imaging systems enable early-stage detection and characterization of pathological or structural anomalies. This review provides a detailed comparative analysis of microwave imaging systems tailored for three critical applications: breast cancer detection, brain stroke …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 39–48 Read article
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Nano‑Enabled CT for Cancer Imaging: From Molecular Targeting to Image‑Guided Therapy
Abstract: Nano‑enabled computed tomography (CT) exploits high‑atomic‑number (high‑Z) nanomaterials engineered with targeting ligands and therapeutic payloads to enhance contrast, enable molecular imaging, and support image‑guided interventions in oncology. Tumor‑specific nanoprobes such as RGD‑modified gold nanorods, polymer‑coated bismuth nanoparticles, and peptide, antibody, or aptamer‑functionalized platforms can intensify tumor conspicuity, allow early lesion detection and staging, and provide real‑time treatment monitoring. Integration of CT visibility with photothermal, photodynamic, chemo‑, radio‑, and immunotherapeutic functions …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 1, 2025 · pp. 40–49 Read article
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Utilizing circulation-derived cancer cells to evaluate patients with surgically treated stages I–IIIA NSCLC throughout the preoperative phase
Abstract: Context: When a tumor is considered resectable, surgery is viewed as the primary treatment approach for both early-stage and locally advanced non-small cell lung cancer (NSCLC). One of the most exciting areas of cancer research in the past ten years is liquid biopsy, which offers a practical non-invasive method for cancer detection and tracking. Circulating tumor cells (CTCs) have been linked to a worse prognosis and increased chance of relapse …
Published in Research and Reviews : Journal of Surgery · Vol. 13, Issue 3, 2024 · pp. 17–28 Read article
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Dual-Stream Deep Learning Framework for Brain CT Image Classification and Implications for Polymer Composite Neuro Implant Evaluation
Abstract: Early and accurate classification of brain CT images is critical for diagnosing conditions such as aneurysms, tumors, and related lesions. We present a dual-stream image-classification framework that fuses convolutional neural network (CNN) features with handcrafted Histogram of Oriented Gradients (HOG) descriptors to jointly capture global semantics and local textural cues. The pipeline begins with modality unification via pixel-wise averaging to form a fused input, which is then processed in parallel …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 172–179 Read article
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A Conceptual Framework for AI-Integrated Metabolomics in Predictive Health Systems for Resource-Constrained Environments
Abstract: The increasing prevalence of non-communicable diseases (NCDs) continues to place a significant strain on healthcare systems, particularly in low- and middle-income regions where access to early diagnostic infrastructure is limited. Conventional healthcare approaches remain largely reactive, often detecting diseases at advanced stages when treatment effectiveness is reduced. This challenge underscores the need for predictive, cost-effective, and data-driven healthcare solutions. This study presents a conceptual framework that integrates metabolomics with artificial …
Published in Emerging Trends in Metabolites · Vol. 3, Issue 2, 2026 Read article
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Disease Prediction Using Ensemble Learning Models: A Comprehensive Approach
Abstract: In recent years, ensemble learning techniques have become pivotal in advancing predictive analytics within healthcare, particularly for early disease detection. The inherent variability and complexity of medical data, often characterized by high dimensionality, class imbalance, and noise, make it challenging for standalone classifiers to maintain high predictive accuracy. Ensemble learning, by integrating multiple models through bagging, boosting, or stacking, offers a more robust and generalizable approach. This study explores the …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 3, 2025 · pp. 26–33 Read article
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Brain Tumor Detection by Aggregating Deep Learning and GAN Models for Faster MRI image Synthesis
Abstract: Brain tumors comprise a global health challenge that, in order to be treated and organized, need early and accurate diagnosis. Usually conducted through medical imaging, brain tumor detection techniques have problems of accuracy, efficiency, and confidentiality. Issues of limited datasets, strict privacy laws that provide restrictions on data sharing, and the necessity for specialized expertise on medical image analysis relegates modern methodologies to vulgar charades. For patient prognosis, treatment planning, …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 45–53 Read article