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89 articles for “Clinical features”
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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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Skin Cancer Detection System Based on Machine Learning for Recognition of Cancerous Images
Abstract: Skin cancer ranks among the most prevalent types of cancer globally and poses significant risks when left untreated. Skin cancer arises when abnormal cells proliferate uncontrollably in the skin. This uncontrolled growth can be triggered by genetic mutations, exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds, or various other factors. In this, the early detection of cancer plays a crucial role in treatment and …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 2, 2024 · pp. 1–8 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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Transfer Learning in Deep Learning Models for Medical Imaging: Utilizing Pretrained Models to Improve Performance in Medical Image Analysis
Abstract: Transfer learning is now a trending technique in deep learning, especially in medical imaging. This technique solves landmark problems by utilizing the pre-trained models, including the limited availability of the annotated medical data and the time-consuming computational costs of training deep learning models from scratch. The generalizability of deep models could increase diagnostic precision for specific medical tasks, require fewer samples to train, and take less time to train due …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 67–85 Read article
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Rheumatoid Arthritis and its Relationship with Vitamin D, ESR, and Obesity
Abstract: Recent years have seen a rise in the prevalence of rheumatoid arthritis (RA), a disease marked by the destruction of articular cartilage and ankylosis of the joints, as well as other complications such as diffuse lung inflammation, sclera, pleura, pericardium, and nodular lesions, which are also common in subcutaneous tissue. Reviewing RA symptoms, diagnosis, treatment, and associations with vitamin D, ESR, and obesity was the aim of the study. Even …
Published in International Journal of Toxins and Toxics · Vol. 1, Issue 1, 2024 · pp. 06–12 Read article
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SkinSight: Design and Implementation of an Intelligent Skin Type Detection System
Abstract: Identifying an individual’s skin type accurately is essential for creating personalized dermatological treatments and formulating skincare products that genuinely meet user needs. In this project, a real- time skin type classification system is developed using a combination of convolutional neural networks (CNNs) and modern computer vision techniques. The system processes live video streams, isolates the facial region through Haar cascade–based detection, and applies a series of preprocessing steps to enhance …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 35–45 Read article
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Machine Learning-Based Approach for Heart Disease Prediction
Abstract: Heart disease is a significant global health challenge, with early diagnosis and prediction being essential for reducing mortality rates. Machine Learning (ML), an efficiently developing field within Artificial Intelligence, provides innovative methods for analyzing complex clinical data to predict heart disease. This review examines the basic machine learning techniques, data, and metrics used in cardiovascular disease prediction. It explores the role of supervised learning, such as decision trees and logistic …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 64–73 Read article
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Graphene Based Electronic Skin for Wearable Health Monitoring and Human– review on Machine Interaction, Materials, Structures and AI Integration
Abstract: Graphene-based electronic skin (e-skin) has emerged as a transformative technology for next-generation wearable health monitoring and advanced human–machine interaction (HMI). Owing to its outstanding electrical conductivity, mechanical flexibility, atomic-scale thickness, and biocompatibility, graphene enables the fabrication of ultrathin, conformal, and multifunctional sensors capable of mimicking the sensory functions of natural human skin. Over the past decade, research in this domain has progressed rapidly across four interconnected fronts: material synthesis and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Stretching Boundaries: A Comprehensive Review of Ehlers-Danlos Syndrome and its Subtypes
Abstract: The Ehlers-Danlos syndromes (EDS) encompass 13 inheritable disorders affecting connective tissue. These conditions arise from genetic alterations impacting the structure of connective tissue. Every variant of Ehlers-Danlos syndrome (EDS) exhibits distinct features and has specific diagnostic criteria. While certain traits such as joint hypermobility, skin hyperextensibility, and tissue fragility are common across all types of EDS. The range of clinical presentations spans from minor skin and joint looseness to severe …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 2, Issue 1, 2024 · pp. 44–57 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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A Hybrid Machine Learning Approach for Cardiovascular Disease Prediction
Abstract: Heart disease ranks among the top causes of death globally. Accurately predicting cardiovascular conditions has become a key challenge in the realm of clinical data analysis. It has been shown that machine learning is an effective means of assisting with predicting and decision-making based on the large volume of data produced by the medical industry. In this study, we describe a unique approach that increases the prediction accuracy of heart-related …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 69–75 Read article
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A Comprehensive Review of Machine Learning and Explainable AI Techniques for Disease Prediction Systems
Abstract: Large amounts of diverse medical data have been produced because of the quick development of digital healthcare systems, offering substantial chances to use machine learning methods for clinical decision support and illness prediction. By identifying intricate patterns in clinical data, machine learning-based models have shown great promise in early disease detection, risk assessment, and personalised healthcare. However, issues with transparency, interpretability, and reliability have been brought up by the growing …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
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Diabetes Prediction Using ML Techniques
Abstract: Diabetes mellitus, commonly referred to as diabetes, denotes a cluster of prevalent endocrine disorders characterized by persistent elevated levels of blood sugar. Diabetes is classified into two main types: type 1 and type 2. Type 1 diabetes arises when the body is unable to produce insulin, while type 2 diabetes involves either insulin resistance or insufficient insulin production. Early detection and intervention are essential to reduce its harmful impacts. The …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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Predictive Modeling of Polymer Composites for Medical Implants Using Artificial Intelligence Techniques
Abstract: The use of polymers in biomaterials was now key to designing the next generation of medical implants, which need to be strong and also compatible with living tissue. Tests for biocompatibility, such as those done in the laboratory and by doing experiments on animals, require much time and many resources, so the need for computer-based approaches becomes clear. An artificial intelligence approach was provided in this study to determine how …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 665–692 Read article
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Exploring the Development of AI Models Using Open-Source Tools to Predict Patient Outcomes and Optimize Treatment Plans
Abstract: Integrating artificial intelligence (AI) into healthcare offers a transformative opportunity to enhance patient care and clinical decision-making. Through the use of predictive analytics, AI can significantly enhance the accuracy of outcome predictions and assist in developing personalized treatment plans that cater to each patient’s specific needs. This paper delves into the development of AI models using open-source tools, which are increasingly favored for their accessibility, collaborative nature, and capacity for …
Published in Journal of Open Source Developments · Vol. 11, Issue 3, 2024 · pp. 37–49 Read article
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Uterine Leiomyosarcoma: A Diagnostic Dilemma
Abstract: Tumours that fall under the category of uterine malignancies include carcinosarcomas, leiomyosarcomas, endometrial stromal sarcomas, and undifferentiated sarcomas. Of them, leiomyosarcoma is the most common subtype, while still quite uncommon—it accounts for 1% to 2% of uterine cancers. Since postmenopausal bleeding is typically present in leiomyosarcomas, prompt detection is essential for successful treatment. This case study features a 50-year-old female patient who had postmenopausal bleeding, which is a common sign …
Published in International Journal of Pathogens · Vol. 1, Issue 1, 2024 · pp. 38–42 Read article
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Artificial Intelligence based Point of Care Device in Advanced Medical Diagnostic Techniques
Abstract: Application of Point-of-Care Testing (POCT) at medical sites provides instant diagnostic results that help doctors make quick decisions for patient care. The traditional point-of-care testing equipment faces restrictions because they test single parameters and experience calibration problems in addition to inefficient data management systems. POCT technology benefits from the integration of Artificial Intelligence (AI) which creates a novel system to solve current operational limitations. The presented study introduces an intelligent …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 2, 2025 Read article
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Pharmacophore mapping, 3D QSAR, docking, and ADME prediction studies of novel Benzothiazinone derivatives
Abstract: Background Tuberculosis is a major public health concern worldwide which is caused by Mycobacterium tuberculosis. DprE1 (Decaprenyl Phosphoryl Ribose 2’- Epimerase) is the most challenging target for development of novel anti- tubercular agents because it is a small protein and located into cytoplasmic membrane. So, novel anti-TB drugs did not bound effectively with it. DprE1 catalyzes the oxidation of the 2’ hydroxyl group of DPR (Decaprenyl Phosphoryl D- Ribose) …
Published in International Journal of Antibiotics · Vol. 1, Issue 1, 2024 · pp. 59–82 Read article
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Blockchain for Secure Health Records in India: Aligning with Ayushman Bharat
Abstract: India’s healthcare ecosystem continues to face significant hurdles, particularly in the efficient management, protection, and accessibility of patient health records. For decades, medical data in the country has remained scattered across institutions, recorded in incompatible formats, and stored in systems that rarely communicate with each other. These gaps not only slow down clinical decision-making but also increase exposure to data breaches and other cybersecurity risks. In this context, blockchain technology …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 1, 2026 · pp. 01–05 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article