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73 articles for “medical image diagnosis”
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Path Lab-AI: An Autonomous Framework for Error-Free Histopathology Slide Interpretation
Abstract: Path Lab-AI represents a fully autonomous platform for the analysis of histopathology slides with circumscribed structures, designed to obtain highly accurate results using diagnostic methods and avoiding the usual limitations of standard microscopy-based pathology. Leveraging recent deep learning and whole slide image (WSI) analysis innovations, our system takes advantage of automated WSI ingestion along with pre-processing steps to account for staining variability, remove artifacts, and localize tissue from background. Such …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 19–30 Read article
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Classification and Detection of Brain Tumor using Convolutional Neural Network
Abstract: Tumors are masses created when brain cells multiply uncontrollably. A brain tumor is the medical term for this condition. Brain tumors are a serious and aggressive disease that can lead to a reduced life expectancy. Developing a treatment plan is essential to raising a patient's standard of living. Tumors in different regions of the body are evaluated using a variety of imaging techniques, with MRI pictures being utilized mostly for …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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Multimodal Disease Detection Using Deep Learning
Abstract: Artificial Intelligence (AI) is playing an increasingly pivotal role in modern healthcare, particularly in improving the speed and accuracy of disease detection. With the evolution of Machine Learning (ML), Deep Learning (DL), and high-performance computing, AI-based solutions are now capable of processing extensive medical datasets, ranging from patient records to diagnostic images, with remarkable efficiency. These systems offer immense potential for early intervention, improved clinical decision-making, and alleviating pressure on …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 129–139 Read article
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The Impact of Nanotechnology in Transforming Neuro-oncology - A Comprehensive Review
Abstract: The treatment of central nervous system (CNS) tumours, including aggressive malignancies like glioblastoma, faces significant challenges. The blood–brain barrier (BBB) blocks nearly 98% of small-molecule drugs from achieving therapeutic levels in the brain, and the heterogeneity of these tumours frequently contributes to treatment resistance and poor outcomes. Traditional approaches, including chemotherapy and radiotherapy, are hindered by systemic toxicity and inadequate drug penetration. Nanotechnology provides a promising alternative, as nanoparticles (NPs) …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 627–637 Read article
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Radiopharmaceuticals use as a nuclear medicine for a Treatment of Disease
Abstract: Radiopharmaceuticals are radioactive substances that contain a bonded radionuclide with the intention of directing the radionuclide to a specific place for treatment or imaging. Radiopharmaceuticals are employed in nuclear medicine for cancer therapy as well as other therapeutic and diagnostic applications. Therefore, the primary goal of this study is to identify the key metal complexes and radioactive elements utilized in radiopharmaceutical applications. The sodium and methylenediphosphonate (MDP-99mTc) complexes, along with …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 17–21 Read article
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A Review of Literature on Breast Cancer: Molecular Insights, Clinical Approaches, and Future Perspectives
Abstract: Breast cancer is the leading cause of morbidity and mortality in women globally. Although both men and women can get the condition, women are more likely to get it, and its prevalence has been rising globally in recent years. The epidemiology, risk factors, pathophysiology, diagnosis, treatment options, and survival rates of breast cancer are all examined in this review of recent research. Breast cancer can show up as a lump …
Published in International Journal of Oncological Nursing and Practices · Vol. 3, Issue 2, 2025 · pp. 15–20 Read article
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Comprehensive Review of Adenoid Cystic Carcinoma: Pathogenesis, Diagnosis, and Emerging Therapeutic Approaches
Abstract: Adenoid cystic carcinoma (ACC)is an infrequent neoplasm, highly malignant, that develops mainly in the salivary glands with the potential to exist in any secretory glandular sites, including the lacrimal glands, breast, and respiratory tract. ACC usually has a benign initial course, but conversely, it is notoriously aggressive in behavior with high incidence of perineural invasion, local recurrence, and distant metastasis, mostly to the lungs. The tumor’s molecular features are characterized …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 3, 2025 · pp. 1–17 Read article
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High-Definition Electroencephalography: A New Horizon in Neurological Pathology Research
Abstract: The advent of high-density electroencephalography (HD-EEG) has catalyzed a paradigm shift in the exploration of neurological pathologies. This editorial underscore its transformative potential in elucidating brain dynamics and refining diagnostic approaches for a spectrum of conditions, spanning from epilepsy and dementia to cognitive impairments in preterm infants. Our objective is to optimize the utility of HD-EEG by emphasizing the imperative for methodological homogenization and fostering collaborative endeavors. The remarkable spatial …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 15–21 Read article
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Advancements in Nanotechnology and Biosensor Integration for Detection and Treatment of Alice in Wonderland Syndrome
Abstract: Alice in Wonderland Syndrome (AIWS) is an uncommon neurological condition characterized by profound distortions in perception. Individuals with AIWS experience altered body image and spatial awareness, often perceiving objects, surroundings, or even their own body as being unusually large, small, or distorted. The condition presents a unique challenge for both diagnosis and management due to its elusive and varied symptoms. This paper explores how advancements in nanotechnology and biosensor integration …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 26, Issue 3, 2024 · pp. 1–12 Read article
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Deep Learning-Based Pneumonia Diagnosis: A Comparative Review of Models and Metrics
Abstract: Pneumonia is a common viral infection that affects a large percentage of people worldwide. It is more common in developing and impoverished areas because of factors like poor sanitation, crowded living quarters, pollution in the environment, and restricted access to medical facilities. In order to improve survival chances and gain access to therapeutic therapies, pneumonia must be diagnosed as soon as possible. A type of artificial intelligence called deep learning …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 Read article
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An Overview of Artificially Generated Neural Networks Inside the Brain’s Structure in an Alzheimer’s Disease Patient
Abstract: Alzheimer’s disease produces significant neuronal loss, while the precise mechanisms and timing are yet unknown. Other types of cell death, such necroptosis, parthanatosis, ferroptosis, and cuproptosis, need further investigation. Based on brain images of people with mild cognitive impairment, this study assesses artificial neural networks (ANNs) used to diagnose and predict Alzheimer’s disease (AD). This research was conducted considering growing recognition among researchers and medical professionals regarding the importance of …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 2, 2025 Read article
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An Expected Cardiovascular Disease Detection Using Deep Learning Techniques
Abstract: Many avoidable deaths globally are caused by CVD, often due to individuals remaining unaware of their risk factors until severe symptoms, such as heart attacks or strokes, appear. This study utilizes retinal images as the dataset to explore the potential of retinal imaging as a non-invasive diagnostic tool for early detection of cardiovascular diseases (CVD). The delay in diagnosis and treatment highlights the need for sophisticated diagnostic instruments that can …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 Read article
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Virtual Method to Predict Dental Disease
Abstract: The integration of technology and medicine in the healthcare domain has led to the emergence of inventive strategies to improve patient care and diagnostics. One such groundbreaking methodology is the utilization of Convolutional Neural Networks (CNNs) within the domain of deep learning, particularly for image recognition and processing tasks. In this paper, we propose a novel approach to image recognition that employs state-of-the-art deep learning algorithms to create a user-friendly …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 8–15 Read article