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174 articles for “medical diagnostics”
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Transforming Rare Disease Diagnosis with AI
Abstract: Artificial intelligence is changing healthcare fast. It is making diagnoses accurate, helping doctors get better results, and streamlining how care works. This paper looks at how AI shows up in healthcare right now – where it is already making a difference, what is working, and what is still tricky. The focus is on machine learning, natural language processing, and computer vision. Particular attention is given to using AI in diagnosing …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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The Role of AI in Modern Healthcare Systems
Abstract: In the Indian pandemic, several issues in the healthcare system have brought to the forefront the imperative of hospitals shifting from manual medical records to computerized healthcare information systems. These solutions offer an effective method for integrating computer-based decision support tools and communicating e-healthcare information. With increasing dependence on AI-based solutions, a strong IT infrastructure is essential for improving healthcare quality, data security, and controlling increasing medical expenses. Advances in …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 69–76 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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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
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The Integration of Artificial Intelligence in Ophthalmology: Augmenting Clinical Decision or Clinical Dependency?
Abstract: The diagnostic accuracy of artificial intelligence (AI) algorithms for glaucoma and diabetic retinopathy screening is on par with or higher than that of skilled doctors. Their acceptance has accelerated due to regulatory clearances, practical implementation in telehealth networks, and growing proof of cost-effectiveness. However, this very success raises a question that the field has been reluctant to address: are we unintentionally undermining the clinical reasoning abilities of the upcoming generation …
Published in Research and Reviews: A Journal of Health Professions · Vol. 16, Issue 1, 2026 · pp. 31–34 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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Clinicians’ role in the prevention and management of neonatal candidiasis in Punjab: challenges and opportunities.
Abstract: Background: Neonatal candidiasis is a growing concern in Punjab, particularly among newborns in neonatal intensive care units. The increasing prevalence poses significant risks to neonatal health, highlighting the need for effective management and prevention strategies. Objective: This study aims to explore the role of clinicians in preventing and managing neonatal candidiasis in Punjab while identifying the key challenges they face in clinical practice. Methods: A structured questionnaire was distributed to …
Published in Recent Trends in Infectious Diseases · Vol. 2, Issue 2, 2025 · pp. 26–33 Read article
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Medical Science in the Digital Era: A Comprehensive Study on Computing in Healthcare
Abstract: Adding computers to medical science has changed how healthcare is delivered, how research is done, and how well patients do. This article talks about the many ways that computer technology is used in modern medicine, such as for diagnostic imaging, electronic health records (EHRs), telemedicine, surgical robotics, and research that is based on data. Improvements in artificial intelligence (AI) and machine learning have made it possible to make more accurate …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 Read article
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A Literature Review on Internet of Medical Things
Abstract: Artificial Intelligence (AI) is transforming healthcare by improving diagnostics, treatment planning, and patient management through data-driven insights and automation. The Internet of Medical Things (IoMT) represents a significant shift in modern healthcare, enabling real-time patient monitoring, data-driven decision-making, and enhanced medical outcomes. This literature review explores the architecture of IoMT, including perception layer, network layer, transport layer and application layer. It also thoroughly explores key challenges like ensuring data security, …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 23–34 Read article
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A Review on Nano-emulsion for Delivery of Anti-cancer Drugs
Abstract: Cancer disease is characterized by abnormal cell growth. Malignant growth treatments have progressed significantly, yet there is a requirement for development in particularity and feeling of dread toward foundational harmfulness. Nanotechnology is the reconciliation of nanoscience into medication by the utilization of nanoparticles. The appearance of nanoscience in disease conclusion and treatment will assist clinicians with better surveying and oversee patients and further develop the medical care framework and administrations …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 1, 2024 · pp. 7–13 Read article
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Autonomous Calibration of Medical Devices Using Synthetic Biosignals and Adaptive Learning
Abstract: The accuracy and reliability of modern biomedical diagnostic devices are critically dependent on effective calibration mechanisms capable of handling dynamic physiological and environmental variations. Conventional calibration approaches, which rely on static reference signals and manual adjustments, are inadequate in addressing challenges such as sensor drift, noise interference, motion artifacts, and long-term performance degradation. To overcome these limitations, this research proposes an innovative AI-driven adaptive biosignal simulation and calibration architecture for …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 2, 2026 Read article
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Fuzzy C-Means Clustering for Effective Segmentation and Classification of Brain Tumors in MRI Scans
Abstract: The paper discusses the importance of detecting and classifying brain tumors via MRI for effective treatment. It proposes a framework utilizing the Fuzzy C-means clustering algorithm for segmentation, demonstrating improved performance through real dataset validation. The model is trained on a large, annotated MRI dataset to identify and classify different tumor types, enabling machine learning-based classification into benign and malignant tumors. The MATLAB-based solution automates brain tumor feature extraction, aiding …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 23–28 Read article
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Role of Fluid Engineering in Biomedical and Healthcare Systems: A Comprehensive Review
Abstract: Fluid engineering — the study and application of fluid behavior, transport, and interaction — has become a cornerstone of modern biomedical and healthcare systems. This review synthesizes the multifaceted roles fluid engineering plays across diagnostics, therapeutics, biomedical devices, and physiological modeling. Micro-fluidics enables precise manipulation of microliter and nanoliter volumes, facilitating rapid point-of-care diagnostics, high-throughput screening, and the fabrication of uniform nano particles for targeted drug delivery. In cardiovascular medicine, …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 1–5 Read article
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Study about Important on why the Phenomenon of Light Propagation in Microstructure on Anisotropy is Important
Abstract: Here we want to explain the phenomenon of light propagation in a subtle structure the information of which is shown here. So here we investigated the phenomenon dependence of light diffusion in human dentin on microstructure. The main scatter tubes are found in the dentin, which can be estimated to be shaped like long cylinders. So here we calculated the scattering of electromagnetic waves through an infinitely long cylinder and …
Published in Research & Reviews : Journal of Physics Read article
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DR. REVIVE: An AI-Powered Medical Recommendation System for Optimised Resources and Improved Patient Care
Abstract: Dr. Revive is an AI-powered medical recommendation system designed to enhance virtual healthcare interactions by connecting patients, doctors, and healthcare stakeholders. Leveraging advanced machine learning algorithms, it analyses user-reported symptoms to provide initial medical recommendations, serving as a reliable first point of guidance. With access to a comprehensive medical database, the platform delivers accurate and timely advice, empowering patients while supporting healthcare professionals with data-driven decision-making. By offering a complete …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 1–10 Read article
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Integrating Traditional Medicine with Modern Health Practices
Abstract: Traditional medicine has been an integral part of global healthcare for centuries, rooted in cultural heritage, and natural remedies. However, with advancements in modern healthcare practices, a divide has formed between traditional and contemporary approaches. This paper explores the potential integration of traditional medicine with modern health practices, emphasizing evidence-based benefits, challenges in harmonization, and policy frameworks for effective collaboration. Through an interdisciplinary analysis, we argue that integrating these systems …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 12, Issue 3, 2025 · pp. 20–26 Read article
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U-Net Based Approach for Automated Brain Tumor Classification
Abstract: Brain tumor detection and identification play vital roles in diagnostic procedures in the field of medicine, with the conventional analysis of MRI images requiring a lot of time and also subject to variability. The proposed study involves the use of a CNN-U-Net based approach for brain tumor detection and identification automatically. The study uses a database of 3,064 contrast-enhanced T1-weighted MRI images from 233 patients with the tumors of meningioma, …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 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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Epigenetic Modifications in Health, Disease, and Precision Therapeutics (From Genome to Epigenome)
Abstract: Introduction: Epigenetic alterations play a crucial role in regulating gene expression in both normal physiological and disease states. These reversible modifications—such as DNA methylation, histone acetylation, phosphorylation, ubiquitination, and chromatin remodelling—are increasingly implicated in complex diseases including cancer and neurodegenerative disorders. Despite advances in standard therapeutic approaches, patient responses remain variable, largely due to genetic heterogeneity and epigenetic dysregulation. This highlights the need for incorporating epigenetic understanding into personalized medicine. …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 Read article
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Artificial Intelligence for Improved Healthcare: A Case Study and Applications
Abstract: Artificial intelligence (AI) in healthcare ushers in a revolutionary period of innovation, but it also brings with it significant ethical dilemmas. This paper explores the complex relationship between AI and healthcare, emphasizing both its useful applications and the moral conundrums that arise. Ethical issues span a wide range, including patient privacy, transparency, accountability, and the unintentional reinforcement of biases in AI algorithms. Privacy concerns take center stage as healthcare providers …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 1–12 Read article