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73 articles for “medical image diagnosis”
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Bioconjugates and Biohybrid Polymers: Intricate Cellular Integration Methods and Sophisticated Biofunctionalization Techniques for Tailored Properties in Medical Contexts
Abstract: Bioconjugates are made when biological molecules are covalently linked to manufactured polymers. They can be used in many ways for imaging, diagnosis, and specific drug delivery. Getting perfect cellular fusion is very important for how well they work. Biomolecules can be attached to polymer scaffolds in a controlled way using techniques like click chemistry and site-specific conjugation. This makes sure that the molecules connect optimally with their biological targets. Using …
Published in Journal of Polymer & Composites · Vol. 12, Issue 3, 2024 · pp. 227–243 Read article
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Role of Artificial Intelligence in Simulation and Therapeutics in Neurodegenerative Diseases
Abstract: Neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, etc., are a cause of significant mortality rates due to a lack of curative treatments and their complex nature. Traditional therapeutic methodologies have several disadvantages such as slow diagnosis and a lack of effective treatments. They mainly focused on the management of the disease rather than curing it. The integration of artificial intelligence in the simulation and therapeutics of neurodegenerative …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 19–29 Read article
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A Comparative Study of different Techniques to predict Maternal Morbidity and Mortality Model
Abstract: Artificial intelligence (AI) encompasses a range of techniques, including machine learning and deep learning, which are increasingly utilized in the healthcare sector for tasks such as disease diagnosis and drug discovery. To achieve accurate disease diagnosis through AI, it is essential to integrate data from multiple medical sources, including ultrasound imaging, magnetic resonance imaging (MRI), mammography, genomics, and computed tomography (CT) scans, among others. This article presents a comprehensive review …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 1, 2025 Read article
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Cartridge-Based Nucleic Acid Amplification for Rapid Tuberculosis Diagnosis
Abstract: In terms of public health, tuberculosis continues to have a significant impact on people's lives. The process of determining the underlying cause of a sickness or condition in a patient is known as clinical diagnosis. It entails the use of numerous diagnostic methods, including physical examinations, laboratory testing, and imaging procedures for medical purposes. Smear microscopy, which are frequently utilized, have poor sensitivity and lengthy turnaround times, respectively. An innovative, …
Published in International Journal of Pathogens · Vol. 1, Issue 1, 2024 · pp. 43–48 Read article
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Study on Brain Tumor Detection Using Morphological Operations in MATLAB with Graphical User Interface (GUI)
Abstract: Brain tumor detection plays a crucial role in early diagnosis and effective treatment planning. This research presents a MATLAB-based Graphical User Interface (GUI) for Brain Tumor Detection, incorporating a comprehensive pipeline of image processing techniques. The GUI provides a user-friendly platform, empowering medical professionals to accurately and efficiently analyze MRI brain scans. The GUI begins with text removal to eliminate any textual artifacts that may be present in the MRI …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 24–31 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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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
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Deep Learning Based Detection and Classification of Brain Tumors Using MRI Images
Abstract: Brain tumor detection using magnetic resonance imaging (MRI) is a critical task in the early detection and treatment of brain tumors. Manual analysis of brain tumor detection using MRI is a tedious task that requires expertise in the field. Therefore, this study proposes a deep learning-based approach for brain tumor detection and classification using Convolutional Neural Networks (CNN). The proposed approach preprocesses the MRI image using normalization, resizing, and noise …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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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
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The Role of Artificial Intelligence and Machine Learning in Redefining Global Healthcare Systems and Advancing Medical Innovation
Abstract: Health Services are being revolutionized with AI and ML through improved accuracy, efficiency and accessibility in the delivery of health care. With AI and ML, it is now possible for health care professionals to assess varying amounts of complex clinical data in a relatively short amount of time, therefore, creating opportunities for early detection of disease, increasing the odds of accurate diagnosis, and improving the ability to make informed clinical …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 14–19 Read article
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Deep Learning Applications in Bone Fracture Detection for Improved Radiographic Diagnostics
Abstract: Bone fracture detection is a critical aspect of medical diagnostics, traditionally relying on manual interpretation of radiographic images by experienced radiologists. This discipline has undergone a revolution with the introduction of machine learning (ML), which can improve accuracy, shorten diagnosis times, and lessen human error. This study investigates the use of different machine learning methods to enhance and automate the identification of bone fractures in radiography pictures. We utilized a …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 17–22 Read article
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The Early Brain Hemorrhage Prediction System Using Machine Learning
Abstract: Brain hemorrhage is a critical medical emergency that requires immediate attention, as delays in diagnosis can result in severe neurological damage or death. The condition involves bleeding within or around brain tissues, leading to increased intracranial pressure and disruption of normal brain function. Although imaging techniques such as CT scans and MRI provide accurate diagnosis, their availability is limited in emergency and rural settings. In recent years, machine learning has …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 Read article
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Magnetic Nanopolymer: Applications and Challenges in Medical Imaging and Theranostics
Abstract: Biopolymers are valuable complex materials. They attract attentions of many scientists, engineers and medical professionals’ for application research. In this research, an assessment of emerging Nanopolymers including magnetic nanopolymer is focused. Hence, sources, magnetic properties, and biomedical application of such polymers are given attention. As ordinary polymers, nano sized biopolymers are visualized as natural and synthetic polymers. However, more emphasis is given to green synthesized magnetic polymer, particularly magnetic Chitosan …
Published in International Journal of Crystalline Materials · Vol. 2, Issue 1, 2025 · pp. 11–21 Read article
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Artificial Intelligence in Diagnostics: Advancements, Challenges, and Future Prospects
Abstract: AI is changing (and will change) healthcare as we know it, and diagnostics might be the specialty that feels the most discomfort. Artificial intelligence-based analytical systems are facilitating the detection, diagnosis, and treatment of a variety of diseases, with better accuracy, speed, and results. Now, this abstract investigates the role of AI in diagnostics, scouring its elements, landmark techniques, transformative impact and future overview. This article explains AI and discusses …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 8–17 Read article
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Systematic Review on: Peptic Ulcer and Its Management
Abstract: Peptic ulcer disease (PUD), which affects 5–10% of people worldwide, is still a significant global health concern. Gastric acid and pepsin's corrosive effects cause mucosal injury in the stomach, duodenum, or lower oesophagus. Long-term use of nonsteroidal anti-inflammatory drugs (NSAIDs) and Helicobacter pylori infection are the primary reasons. This review's goal is to examine PUD's aetiology, risk factors, pathophysiology, clinical symptoms, diagnostic methods, and evidence-based treatment modalities. PubMed, Google Scholar, …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 1, 2026 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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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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Unresolved and misdiagnosed of floating sensation in young man
Abstract: Persistent Postural-Perceptual Dizziness (PPPD) stands out as a prevalent peripheral vestibular disorder, earning its recognition in the International Classification of Vestibular Disorders in 2017. Characterized by chronicity, this condition manifests symptoms persisting for more than three months, encompassing a disconcerting array such as a floating sensation, unsteadiness, and dizziness. Notably, individuals afflicted with PPPD often report symptom exacerbation following prolonged standing, self-initiated motion, or exposure to dynamic visual stimuli. This …
Published in International Journal of Brain Sciences · Vol. 1, Issue 1, 2024 · pp. 1–4 Read article
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Brain Tumor Detection Using RestNet50 Architecture
Abstract: This paper presents a novel deep learning model for brain tumor diagnosis from MRI scans on the basis of ResNet50 with some modifications. Optimizing the modified layers and pre-trained ResNet50 for improved diagnostic accuracy and reliability in real-world clinical settings is one of the key contributions of this paper. The model was trained on an extremely well-balanced data of 2,577 MRI scans, which were split equally among the tumor and …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 1–13 Read article
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Retinal Disease Detection Using Deep CNN
Abstract: Age-related macular degeneration, glaucoma, and diabetic retinopathy are the three main causes of blindness in the globe. To avoid visual loss, early identification and treatment of these disorders are essential. The goal of this research is to create an automated method for detecting retinal diseases by analyzing retinal fundus pictures with machine learning techniques. Python and the Tkinter package for the graphical user interface are used in the construction of …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 46–50 Read article