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19 articles for “computer-aided diagnosis”
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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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Predictive Modeling System for Automated Skin Lesion Classification Using Deep Neural Networks and Voting Ensembles
Abstract: Skin cancer is one of the most prevalent cancers globally. Early and accurate diagnosis is critical for timely treatment and improved prognosis. This study presents a predictive modeling system for automated classification of skin lesions from dermoscopic images using deep neural networks and voting ensemble techniques. A customized 16-layer convolutional neural network architecture is developed for feature learning from lesion images. The concept of horizontal voting ensemble is implemented by …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 29–35 Read article
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Computer Aided Circuit Design for Diagnosis of Dust Impact on Solar Panels
Abstract: AbstractSolar panels have come up as a promising methodology for extracting solar energy and yielding electricity. However, there exist many barriers in its path to become an indispensable part of today's era. The decreasing panel efficiency due to several factors such as temperature, irradiance, photoactive material, dust, panel orientation, is an issue of concern. Amongst these, dust is the least acknowledged, yet the most crucial parameter responsible for deteriorating panel …
Published in Journal of Electronic Design Technology · Vol. 9, Issue 3, 2018 · pp. 11–16 Read article
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Alzheimer disorders diagnosis system design using machine learning for EEG signal
Abstract: The diagnosis of Alzheimer's disorders (AD), a prevalent neurological disorder, can created by utilising a range of therapeutic methods, including the electroencephalogram (EEG), which has been especially successful in the past. The objective for this study is to develop a computer-aided diagnosis tool which may recognize AD from EEG data. The EEG information was cleaned up with a band-pass elliptic digital filter to remove any interference or disruptions. The filtered …
Published in Journal of Control & Instrumentation Read article
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Boundary Localization of Optic Disc using Pixel Level Deviation in Retinal Fundus Image
Abstract: In automated computer-aided diagnosis (CAD) approach for Diabetic retinopathy (DR) detection and monitoring, optic disc (OD) localization is the first and fundamental task for further processing of retinal fundus image. Identification of OD area is complex, as it attains the similar pathological blood vessels characteristics such as intensity variations and texture pattern. This paper presents a simple approach for the outer boundary localization of OD based on pixel level variations, …
Published in Research and Reviews: A Journal of Health Professions · Vol. 8, Issue 2, 2018 · pp. 14–18 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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Alzheimer disorders diagnosis system design using machine learning for EEG signal
Abstract: The diagnosis of Alzheimer's disorders (AD), a prevalent neurological disorder, can created by utilising a range of therapeutic methods, including the electroencephalogram (EEG), which has been especially successful in the past. The objective for this study is to develop a computer-aided diagnosis tool which may recognize AD from EEG data. The EEG information was cleaned up with a band-pass elliptic digital filter to remove any interference or disruptions. The filtered …
Published in Journal of Control & Instrumentation · Vol. 14, Issue 1, 2023 · pp. 9–22 Read article
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Feature Extraction to Detect Diabetic Retinopathy and Glaucoma in Fundus Image
Abstract: Visual impairment due to various eye-related diseases can be largely prevented through regular fundus colour image screening. Large scale screening of the retinal image in the early stages is crucial to disease diagnosis. It is reported that the number of ophthalmologist ratios is very low. Hence, the computer-aided screening is required where the diagnosis of disease from an image is done from the main features of the fundus image. In …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 7, Issue 1, 2018 · pp. 9–12 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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A Review on Detection of Autism Spectrum Disorder Using Signal Processing
Abstract: AbstractAutism is a neural developmental disability associated with impairments in communication and social interaction; it can be detected by various methods such as Magnetic Resonance Imaging (MRI) and Electroencephalography (EEG). MRI is a technique which captures the image of various sections of brain. It is categorised as structural MRI (sMRI) and functional MRI (fMRI). The detection involves capturing the image, removing the unwanted regions of brain, segmenting the images and …
Published in Current Trends in Signal Processing · Vol. 8, Issue 2, 2018 · pp. 12–24 Read article
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Advances in Lung Cancer Detection and Diagnosis: An Integrative Approach Using Computational Chemistry, Statistics, Bioinformatics, Artificial Intelligence, and Machine Learning
Abstract: Lung cancer is still one of the most common and lethal cancers globally, accounting for more than a million deaths each year. Prompt detection is important, and imaging techniques like chest X-rays, MRIs, PETs, CTs, and molecular imaging have become important tools. But still, even though all these techniques do not provide an accurate classification of the lesion, they have led to the development of computer-based high-resolution image analysis. Computer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Enhancing Image Classification Performance with Deep Neural Networks
Abstract: Classifying images is useful in many domains, including the study of plant diseases and the analysis of human expressions. Image categorization employing the idea of a “deep neural network” helps to compact otherwise cumbersome photos. It is possible to classify images by using the idea of a “deep neural network”. Self-driving cars, medical diagnosis, automatic translation, etc., all make use of Deep Neural Networks. Recently, excellent results have been achieved …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 1, 2024 · pp. 13–23 Read article
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Importance of Clinical Evaluation in Nasopalatine Duct Cyst: A Case Report
Abstract: Present case report shows the importance of proper history taking, clinical evaluation such as swelling in the midline of the anterior palate, midline diastema and radiographical diagnostic aid like cone beam computed tomography which revealed a large well circumscribed oval shaped or heart shaped periapical radiolucency, resorption of antero-medial cortex of naso-palatine canal with an involvement of neighboring anatomical structures like upper impacted incisors helps in proper diagnosis of non-odontogenic …
Published in Research and Reviews: A Journal of Dentistry · Vol. 7, Issue 1, 2016 · pp. 7–11 Read article
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Detection and Classification of Diabetic Retinopathy Using Deep Learning Techniques
Abstract: This project delves into the evaluation of three prominent deep learning architectures Basic CNN, ResNet, and DenseNet for their efficacy in detecting diabetic retinopathy from retinal images. Utilizing a diverse dataset, the study employs standard deep learning frameworks to train and validate each model. The focus extends to exploring the potential benefits of transfer learning on a limited dataset. Evaluation metrics like specificity, sensitivity, and accuracy are employed for a …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 64–69 Read article
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Managing Carpal Tunnel Syndrome: Insights into Symptoms and Relief
Abstract: Carpal tunnel syndrome (CTS) is a prevalent and concerning issue affecting the wrist and hand, arising from the compression of the median nerve within the carpal tunnel. This compression results in a spectrum of distressing symptoms, including numbness, tingling, weakness, and discomfort, particularly in the thumb, index, and middle fingers. Despite its frequent association with repetitive hand movements and prolonged use of computers or handheld devices, CTS can stem from …
Published in International Journal of Orthopedic Nursing and Practices · Vol. 1, Issue 2, 2023 · pp. 6–12 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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Retroperitoneal Lymphatic Cyst Mimicking Appendicular Mucocele and Lymphangioma
Abstract: Chronic pain in right lower abdominal quadrant is a common entity in young adults in surgical cases. We report a case of 16 years old female who presented with complaints of pain in right lower quadrant and high grade fever. CECT (Contrast Enhanced Computed Tomography) abdomen suggested the possibility of giant mucocele of appendix and other cystic lesions such as retroperitoneal lymphangioma. USG (ultrasonography) suggested possibility of lymphangioma. Exploratory laparotomy …
Published in Research and Reviews : Journal of Surgery · Vol. 4, Issue 1, 2015 · pp. 16–19 Read article
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A Comparative Machine Learning Framework for Early Prediction of Liver Cancer Using Clinical Attributes
Abstract: One of the main causes of cancer-related death globally is liver cancer, and improving patient outcomes depends heavily on early detection. However, low contrast, noise, organ similarity, and tumor shape and size variability make it difficult to accurately identify and segment liver tumors from medical imaging. Automated liver cancer diagnosis, segmentation, and prognosis have been greatly improved by recent developments in artificial intelligence (AI), especially deep learning. This work presents …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 · pp. 39–47 Read article
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Computational Analysis of Non-Newtonian Blood Flow through Bifurcated Coronary Artery: Insights into Hemodynamics and Wall Shear Stress
Abstract: This abstract presents a study on the computational fluid dynamics (CFD) simulations of blood flow through a bifurcated coronary artery using non-Newtonian fluid model. The objective of this study is to investigate the hemodynamic characteristics in Bifurcated Coronary artery. The methodology involved the utilization of ANSYS SpaceClaim software for creating a geometric model of the bifurcated coronary artery. A mesh independent study was conducted to ensure the accuracy and reliability …
Published in Journal of Polymer & Composites · Vol. 11, Issue 13, 2023 · pp. 160–168 Read article