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129 articles for “Diagnostic Accuracy”
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Artificial Intelligence in Microbiological Research: Methods, Applications and Implications
Abstract: Artificial Intelligence (AI) is revolutionising microbiological research by enabling the rapid analysis of complex biological data and improving the accuracy, efficiency, and reliability of scientific investigations. Recent advances in machine learning, deep learning, and bioinformatics have transformed AI into a powerful tool for studying microorganisms, their genetic composition, evolutionary patterns, and interactions with hosts and the environment. AI-driven computational models can process large and complex datasets far more efficiently than …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 16, Issue 2, 2026 Read article
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Detection of Brain Tumors from MRI Images Based On Development of Thinking Computer Systems Techniques
Abstract: Brain tumors are one of the common diseases of the nervous system and have great harm to human health, and even lead to death. The detection, segmentation, and extraction of contaminated tumour regions from Magnetic Resonance Imaging (MRI) pictures are major problems; yet, a repetitive and time-consuming task performed by radiologists or clinical experts relies on their experience. The many anatomical structures of the human organ can be imagined using …
Published in Current Trends in Signal Processing Read article
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Role of Therapeutic Index for Local Infections Score in Wound Assessment
Abstract: Local wound infections pose a significant challenge, often detected later, leading to complications like systemic infections. Global nomenclature lacks uniformity, resulting in varied treatments for similar diagnoses. Early intervention is crucial, advocating for local antimicrobial therapy with diverse active agents to avoid systemic antibiotics and mitigate bacterial resistance. The Therapeutic Index for Local Infections (TILI) score, innovated by the German society Initiative Chronis Che Wenden (ICW), emerges as a pivotal …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 1, 2024 · pp. 44–48 Read article
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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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Towards Intelligent Healthcare: Artificial Intelligence’s Impact on Healthcare
Abstract: Artificial Intelligence (AI) stands as a transformative force within healthcare, offering multifaceted support to various processes and medical professionals. This comprehensive study investigates the extensive array of AI applications and its potential to reshape the healthcare landscape. Specifically, it examines the utilization of deep-learning methodologies in harnessing vast medical datasets to enhance healthcare provision. Expanding beyond theoretical discussions, this study scrutinizes AI's role in breast cancer, seizure, and tumor detection, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 77–83 Read article
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Editorial: Advancements in Movement Analysis for Understanding Neurological Disorders
Abstract: Neurological disorders pose a significant challenge, demanding innovative approaches for accurate diagnosis, effective treatment, and deeper understanding. Movement analysis emerges as a powerful tool, offering a quantitative window into the complexities of motor function. This editorial delves into the transformative impact of movement analysis on neurological research and clinical practice. Traditional diagnostic methods, reliant on subjective observations, often miss subtle motor impairments, particularly in early disease stages. Movement analysis tackles …
Published in International Journal of Brain Sciences · Vol. 1, Issue 2, 2024 · pp. 28–32 Read article
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Refining Retinal Layer Segmentation in OCT Imaging with Advanced Techniques and Clinical Applications
Abstract: Segmenting retinal layers from Optical Coherence Tomography (OCT) pictures entails locating and separating different retinal layers to offer comprehensive anatomical and pathological information. Age-related macular degeneration, diabetic retinopathy, and glaucoma are among the retinal illnesses for which this procedure is crucial for diagnosis and follow-up. By utilizing preprocessing techniques to improve image quality and applying advanced algorithms—such as intensity-based, gradient-based, and texture-based methods—alongside deep learning approaches, clinicians can accurately measure …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 01–06 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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Survey on Retinal OCT Image Preprocessing, Segmentation, and Deep Learning Based Classification
Abstract: Optical coherence tomography (OCT) is a non-invasive technique that generates high-resolution, detailed cross-sectional images of biological tissues. By utilizing low-coherence interferometry, OCT enables visualization of tissue microstructure with micron-scale resolution, making it useful in various medical fields such as ophthalmology, cardiology, and dermatology. In ophthalmology, OCT is extensively used for diagnosing and monitoring retinal diseases like macular degeneration and diabetic retinopathy, allowing doctors to assess changes in tissue morphology over …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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Evaluation of Small Vessel Disease by Advanced Brain Imaging
Abstract: Studying and comprehending brain small vessel disease requires extensive imaging. Recent applications of cutting-edge brain imaging techniques have led to the discovery of several significant results. Diffusion-weighted MRI studies have demonstrated the diagnostic accuracy of using clinical features alone or in combination with CT scan results to identify small vessel disease as the underlying cause is suboptimal in patients with acute lacunar syndromes. Acute infarcts caused by small vessel disease …
Published in International Journal of Cheminformatics · Vol. 2, Issue 1, 2024 · pp. 15–19 Read article
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Revolutionizing oncology - role of artificial intelligence in early cancer detection and diagnostic advances-A comprehensive review
Abstract: Oncology has experienced a remarkable transformation with the adoption of artificial intelligence (AI), which has greatly enhanced cancer detection and diagnosis. As one of the leading causes of death worldwide, cancer highlights the importance of early detection in improving patient outcomes and survival rates. AI’s ability to analyze vast and complex datasets has enabled groundbreaking innovations in imaging, pathology, biomarker discovery, and predictive analytics. This review highlights key AI-driven advancements …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 1, 2025 · pp. 18–22 Read article
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Artificial Intelligence in intra operative and peri operative management of major oral and maxillofacial surgeries
Abstract: Artificial Intelligence and virtual reality are becoming a part of everyday life and are enhancing our quality of life extensively. It is only natural that the same shall be used in surgery also. The existing body of literature on artificial intelligence (AI) and its integration into various surgical specialties has been extensively reviewed and discussed in this article. These insights, though derived from broader surgical domains, can be effectively translated …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 2, 2025 · pp. 1–5 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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Cervical Leiomyomas: Age associated insights from 3 Year prospective study from Tertiary Care Hospital
Abstract: Cervical leiomyomas are rare benign smooth muscle tumours of cervix, often presenting diagnostic challenges due to their uncommon occurrence and overlapping features with other cervical pathologies. This is a 3-year prospective study involving a total of 460 female subjects who were diagnosed with various gynecologic complications, with a particular focus on cervical leiomyomas. The study aims to provide a comprehensive age-wise distribution of cervical leiomyomas, emphasizing the incidence and prevalence …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 Read article
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Progression of Health and Wellness: Artificial Intelligence (AI) and Deep Learning (DL) for Precision Medicines
Abstract: Deep learning and artificial intelligence in the field of precision medicine is revolutionizing healthcare to make personalized therapeutic approaches desirable based on the unique characteristics of the patient. AI technologies improve diagnostic accuracy by analyzing medical data, spotting patterns and anomalies that human experts may miss. AI-driven models are instrumental in precision medicine, where they can predict patient response to therapies to tailor treatment plans, enhancing outcomes and reducing adverse …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 2, 2025 · pp. 1–5 Read article
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Advances in Polymer-Based Materials for Dental Applications: A Case Study on PVC and Ceramic Coatings in Digital Mouth Mirrors
Abstract: Polymeric materials play a crucial role in modern dentistry, providing improved mechanical properties, biocompatibility, and enhanced functionality in dental instruments. These materials contribute significantly to the advancement of dental tools, ensuring durability, safety, and efficiency. This study explores the application of polyvinyl chloride (PVC), ceramic coatings, and anti-fog polymer layers in the development of a digital mouth mirror. The integration of these materials results in enhanced durability, corrosion resistance, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 244–252 Read article
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Early Detection of Heart Disease using Machine Learning Techniques
Abstract: Coronary illness stays one of the main sources of death around the world. Exact expectations of coronary illness can altogether work on quiet results by empowering early intercession and customized treatment plans. Throughout the course of many recent years, AI (ML) methods have been extensively investigated for anticipating coronary illness, attribuFig to their remarkable capacity to analyze complex data patterns and generate precise predictions based on historical clinical records. With …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 34–45 Read article
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A Review on Applications of Artificial Intelligence (AI) in Parkinsons’s Disease Diagnosis and Treatment and Its Future Challenges
Abstract: Parkinson’s disease (PD) is a long-term, progressive neurodegenerative disorder that mainly occurs in people older than 60 years, affecting nearly 1% of this population. It is chiefly marked by the loss of dopaminergic neurons in the substantia nigra, a crucial brain region responsible for controlling motor functions. The resultant dopamine deficiency significantly disrupts motor control, manifesting in clinical symptoms such as tremors, bradykinesia, muscle rigidity, and postural instability. While PD …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 · pp. 1–15 Read article
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A Systematic Review on The Role of Artificial Intelligence in Assisted Reproductive Technology
Abstract: Artificial Intelligence (AI) has significantly transformed Assisted Reproductive Technology (ART) over the past five years, enhancing diagnostic accuracy, treatment personalization, and overall success rates. AI-driven algorithms and machine learning models have been integrated into various aspects of ART, including sperm selection, embryo grading, and predicting implantation success. Deep learning techniques have improved image-based embryo assessment, reduced human subjectivity and increased efficiency. Additionally, AI-powered predictive analytics have helped optimize ovarian stimulation …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 Read article
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Paediatric Epilepsy: Current Advances in Diagnosis and Management
Abstract: Paediatric epilepsy is one of the most common chronic neurological disorders of childhood, characterised by recurrent unprovoked seizures resulting from abnormal neuronal activity. Accurate diagnosis is essential and is based on a detailed clinical history, seizure semiology, neurological examination, and electroencephalography (EEG), with neuroimaging such as magnetic resonance imaging (MRI) used to identify structural abnormalities. Classification according to seizure type and underlying aetiology genetic, structural, metabolic, immune, infectious, or unknown—guides …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 1, 2026 · pp. 53–68 Read article