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65 articles for “cancer diagnosis”
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Enhancing Cancer Diagnosis: AI/ML Algorithms and Nanotechnology-Based Biosensors for Colorectal Cancer Screening
Abstract: Colorectal cancer (CRC) is one of the most common and deadly cancers worldwide, and enhancing patient outcomes requires early identification. This study explores the potential of nanotechnology- enhanced biosensors and artificial intelligence/machine learning (AI/ML) algorithms to revolutionize colorectal cancer screening and diagnosis. Nanotechnology offers unique opportunities for the development of highly sensitive and specific biosensors capable of detecting cancer biomarkers at an early stage. By incorporating nanomaterials with exceptional optical, …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 26, Issue 1, 2024 · pp. 16–28 Read article
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A Knowledge Graph Approach for Breast Cancer Diagnosis and Data Sharing Platform Implementation in the Context of Human Papillomavirus Infection
Abstract: Background: Breast cancer remains among the most prevalent malignancies in women worldwide, and effective diagnosis and data integration continue to challenge clinical practice. Diagnostic reports from mammography and ultrasound contain rich clinical information that is often under-utilised due to heterogeneous formats and limited data-sharing infrastructure. In the context of human papillomavirus (HPV) infection, which may influence oncogenic pathways and data complexity, advanced computational methods offer new solutions to this problem. …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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Impact of Counseling on Cancer Patient’s Depression Level
Abstract: Introduction: When given the dreaded and possibly fatal cancer diagnosis, patients go through a great deal of pain. Depression is one of the psychiatric problems that can arise after a cancer diagnosis. The purpose of the current research is to evaluate how well counseling therapy can lower depression levels in cancer patients. Methodology: Geetanjali Hospital in Udaipur provided the data for this study, which utilized a single-group, quasi-experimental analysis employing …
Published in International Journal of Oncological Nursing and Practices · Vol. 1, Issue 1, 2023 · pp. 1–5 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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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
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Towards smart cancer care - AI enhanced monitoring and intervention
Abstract: According to estimates from the World Health Organization (WHO) for 2022, cancer is one of the leading causes of mortality, accounting for roughly 16% of all deaths globally. The goal of the cancer community is to improve the lives of those who are impacted by cancer and to cut the cancer death rate in half during the next several years. If cancer is identified early and treated, its impact on …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 1, 2025 · pp. 38–44 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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Ovarian Cancer: Understanding Risk Factors, Diagnosis, and Advances in Treatment
Abstract: Ovarian cancer is a leading cause of cancer-related mortality among women worldwide, often diagnosed at advanced stages due to its subtle early symptoms. Ovarian cancer develops due to a combination of factors, including genetics, environmental influences, and hormonal changes. This article explores the pathophysiology of ovarian cancer, highlighting the genetic mutations, such as BRCA1 and BRCA2, that contribute to its development. It also discusses current diagnostic methods, including imaging techniques …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 Read article
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An Insight into Childhood Malignancy
Abstract: Childhood cancers represent a significant public health concern, affecting a vulnerable population with unique biological and developmental characteristics. The aim of this article is to describe the main causes and different types of malignancies in childhood. By understanding the contributing factors towards malignancy in childhood one can plan for the preventive measures and early diagnosis and treatment modalities can be adopted. Even though the treatment patterns have improved, people are …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 1, 2024 · pp. 07–12 Read article
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An Effective Convolutional Neural Network for Identifying Cancer Blood Disorder Cells Using Microscopic Images
Abstract: Blood, bone marrow, and lymphatic systems are all impacted by hematological cancer is known as a cancer blood disorder. Blood malignancies and various blood disorders pose significant health challenges across all age groups. Early disease detection is essential for effective cancer blood disorder treatment and management. If a blood cancer is not identified in time, it may be hazardous. It results in abnormal white blood cell production by the bone …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 2, 2024 · pp. 29–35 Read article
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Advances in Multiclass Oral Cancer Detection Using Spectroscopic and AI Techniques
Abstract: Oral cancer, primarily OSCC, is still a major health issue worldwide, especially in low-HDI countries. Early diagnosis is essential since survival rates for early detection are much higher than for late-stage detection. However, traditional methods like visual inspection and biopsy are time-consuming, invasive, and rely on the clinician's skill, which is a limitation in accessibility and efficiency. Oral cancer detection has just been revolutionized by recent advances in spectroscopic techniques, …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 3, 2025 · pp. 39–48 Read article
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Literature Review On Nanotechnology In Dentistry
Abstract: Nanotechnology is a relatively new field in dentistry that utilizes nanomaterials, nanorobots, and nanotechnology for diagnosing, treating, and preventing dental diseases. Nanotechnology has revolutionized various fields of dentistry, offering innovative solutions that enhance patient care, improve treatment outcomes, and contribute to the overall advancement of dental science. This cutting-edge technology has found applications in several areas, including restorative dentistry, dental implants, early cancer diagnosis, dental hypersensitivity, and pain management, among …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 2, 2025 · pp. 19–23 Read article
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Biomarkers in Cancer Research: Discovery and Future Directions
Abstract: Biomarkers have transformed the study of cancer, providing critical information regarding prognosis and therapy response and promoting earlier diagnosis. This paper discusses the different parts of cancer biomarkers, starting with their description, classification, and major types, which are the groundwork for understanding their clinical role. The discussion on the development and validation process of biomarkers is then undertaken, focusing on state-of-the-art techniques and the importance of ensuring accuracy and reproducibility. …
Published in Trends in Drug Delivery · Vol. 12, Issue 1, 2025 · pp. 22–26 Read article
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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
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Interpretable Skin Cancer Detection via Optimized CNN Models for Smart Healthcare Solutions
Abstract: Skin cancer is a common and potentially life-threatening condition, highlighting the importance of reliable and efficient diagnostic techniques. Recently, convolutional neural networks (CNNs) have demonstrated significant potential in automating the classification of skin cancer using thermoscopic images. Despite these advancements, the lack of interpretability in these models poses a barrier to their widespread use in clinical settings. In this study, we propose an interpretable CNN architecture optimized for skin cancer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 41–45 Read article
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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Gene Annotation of Cancer Vaccine for Homo sapiens
Abstract: Objectives: Gene annotation helps us to deduce the structural and functional aspects of a gene that encodes for a functional protein in our body. Thus, by determining the coding sequence and gene location we can derive meaningful insights as to what these genes do in our body. In this study, an unknown gene, cancer vaccine for Homo sapiens has been studied and annotated. Methods: This study was based on a …
Published in International Journal of Molecular Biotechnological Research · Vol. 2, Issue 1, 2024 · pp. 1–14 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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Cancer Tumor Markers And Its Latest Trends
Abstract: Almost one in six deaths occurs due to abnormal cell division; these cells are termed cancer cells in general. Cancer cells collaborate to multiply and metastasize. Our aim is to awaken awareness in people to understand their bodies and motivate them for early diagnosis,as cancer is the second leading cause of death after cardiovascular disease. The human body is a marvellous creation in nature; in response to cancer, it creates …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 3, 2024 · pp. 25–38 Read article