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131 articles for “healthcare diagnostics”
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Adoption of Artificial Intelligence in Periodontal Diagnostics: Awareness, Confidence, and Barriers Among Dental Practitioners in India
Abstract: AI has emerged as a transformative tool in healthcare, including periodontics, where it aids in diagnosing periodontal diseases, assessing bone loss, and predicting disease progression. Despite its potential, the adoption of AI in dentistry, particularly in India, remains limited. This study aimed to evaluate the awareness, confidence, and willingness of dental practitioners to adopt AI-based tools in periodontal diagnostics. A cross-sectional survey was conducted among 106 dental practitioners, including general …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 3, 2025 · pp. 27–38 Read article
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Explainable Artificial Intelligence in Personalized Medicine: Emerging Clinical Perspectives
Abstract: The convergence of artificial intelligence (AI) and precision medicine has transformed contemporary healthcare by enabling data-driven clinical decision-making, individualized therapeutic interventions, and predictive diagnostics. However, despite remarkable advances in machine learning (ML) and deep learning (DL), the widespread adoption of AI in healthcare remains constrained by the “black-box” nature of many computational systems. Clinicians, regulatory agencies, and patients increasingly demand transparency, interpretability, and trustworthiness in AI-guided medical recommendations. Explainable Artificial …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 13–29 Read article
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Breast Cancer Detection Using Machine Learning: A Comparative Analysis of Supervised Learning Algorithms
Abstract: Globally, breast cancer remains a predominant cause of mortality among women, highlighting the urgent need for timely and precise diagnostic approaches. This research explores the application of machine learning algorithms—including Logistic Regression, SVM, Naïve Bayes, KNN, and Random Forest—on the Wisconsin Breast Cancer Dataset for effective tumor classification. Key pre-processing steps such as missing value handling, feature scaling, and dimensionality reduction were employed to improve model performance. The study evaluated …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 46–52 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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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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Intellectual Brilliance: Patents and Copyrights in Publications
Abstract: Intellectual property rights play a vital role in safeguarding creativity and innovation, with copyrights and patents being fundamental tools in this process. This study offers an in-depth exploration of these concepts, focusing on their processes, importance, and practical applications, particularly within the healthcare sector. By delving into the nuances of intellectual property, provides valuable insights into how these rights empower creators and innovators to protect their contributions and further global …
Published in International Journal of Sustainability · Vol. 1, Issue 2, 2024 · pp. 6–11 Read article
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Interpretable Skin Cancer Detection via Optimized CNN Models for Smart Healthcare Solutions
Abstract: Skin cancer is a common and potentially life-threatening condition, highlighting the importance of reliable and efficient diagnostic techniques. Recently, convolutional neural networks (CNNs) have demonstrated significant potential in automating the classification of skin cancer using thermoscopic images. Despite these advancements, the lack of interpretability in these models poses a barrier to their widespread use in clinical settings. In this study, we propose an interpretable CNN architecture optimized for skin cancer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 41–45 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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Impact of Therapeutics on Carbapenem-Resistant Acinetobacter baumannii
Abstract: Acinetobacter baumannii, a formidable pathogen in healthcare settings, poses a significant threat due to its propensity to cause nosocomial infections. This bacterium exhibits several attributes that enable it to evade the human body's natural defenses. A. baumannii's remarkable adaptability is highlighted by its ease in acquiring antibiotic resistance determinants, rendering it challenging to treat. Its ability to thrive in hospital environments underscores the urgent need for stringent infection control practices …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 14, Issue 2, 2024 · pp. 1–11 Read article
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Predicting Multiple Diseases Using Machine Learning: A Data-Driven Approach
Abstract: The increasing prevalence of chronic and life-threatening diseases highlights the need for innovative healthcare solutions that enable early detection and proactive management. The Multiple Disease Prediction Platform is a web-based system utilizing machine learning (ML) and deep learning (DL) algorithms to analyze user-inputted health data, generating real-time predictions of potential health risks. By leveraging Python’s Streamlit library, the platform provides an interactive and accessible diagnostic experience, eliminating the need for …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 16–35 Read article
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Intelligent Medical Devices and Robotics in Modern Healthcare: Technological Advancements and Economic Considerations
Abstract: The integration of robots and intelligent medical devices in intensive care units (ICUs) represents a significant advancement in healthcare technology. These systems, including robotic assistants, automated monitoring tools, and AI-powered diagnostic devices, are designed to enhance patient care, streamline workflows, and reduce human error. Robots in the ICU can assist with routine tasks such as medication delivery, patient repositioning, and even basic surgeries, enabling healthcare professionals to focus on critical …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 3, 2024 · pp. 18–27 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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Nanoformulation Strategies: Emerging Innovations in Drug Delivery Systems
Abstract: Nanotechnology is significantly advancing the pharmaceutical industry by introducing nanosystems that improve drug delivery, therapeutic efficacy, and patient outcomes. Various nanosystems-such as liposomes, dendrimers, polymeric nanoparticles, solid lipid nanoparticles, carbon nanotubes, and metallic nanoparticles-offer benefits like enhanced bioavailability, targeted delivery, improved stability, and reduced side effects. Innovative formulation strategies, including surface functionalization, particle size optimization, and use of biodegradable carriers, support controlled and sustained drug release. Additionally, production in non-aqueous …
Published in International Journal of Toxins and Toxics · Vol. 3, Issue 1, 2026 · pp. 54–67 Read article
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Collaborative Care for Diabetic Retinopathy: Integrating Artificial Intelligence and Clinical Pharmacy Services - A Comprehensive Review
Abstract: Background: Diabetic retinopathy (DR) remains the leading cause of blindness among working-age adults globally, affecting approximately 103 million people worldwide. The integration of artificial intelligence (AI) technologies with clinical pharmacy services presents unprecedented opportunities to enhance screening, diagnosis, and management of DR through collaborative care models. Objective: This comprehensive review examines the current landscape of collaborative care approaches for diabetic retinopathy management, focusing on the integration of AI-powered diagnostic tools …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 118–128 Read article
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Heart Disease AI-based Prediction: A Comparative Analysis
Abstract: The present investigation looks at how well various machine learning algorithms predict cardiac disease. Since heart disease is one of the major causes of death worldwide, early detection and precise diagnosis are essential for managing and treating the condition. Our goal is to enhance diagnostic processes and improve patient outcomes by leveraging machine learning techniques. Six widely-used machine learning algorithms are evaluated in this research paper. These algorithms were selected …
Published in Trends in Mechanical Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 21–29 Read article
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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
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Advancing Tropical Medicine: Interdisciplinary Approaches, Innovation, and Health System Strengthening
Abstract: Tropical medicine encompasses a diverse range of infectious diseases prevalent in tropical and subtropical regions, presenting complex challenges to global health. This review offers an extensive examination of critical aspects within tropical medicine, emphasizing recent progress and upcoming avenues of research. Interdisciplinary collaboration is highlighted as essential for addressing the multifaceted nature of tropical diseases, with healthcare professionals, veterinarians, ecologists, epidemiologists, and social scientists working together to tackle complex health …
Published in International Journal of Tropical Medicines · Vol. 1, Issue 2, 2024 · pp. 1–13 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
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Impact of a Structured Educational Program on Awareness of the Janani Shishu Suraksha Yojana (JSSY) Among Expectant Mothers in a Designated Primary Health Center in Bengaluru
Abstract: The Janani Shishu Suraksha Karyakram (JSSK) was launched to offer comprehensive support services including cost-free delivery, transportation, medications, diagnostic services, blood, and nutrition to expectant mothers and ill infants up to a year old at public healthcare facilities. This research utilized a quantitative methodology, adopting a pre-experimental design with a single group evaluated before and after the intervention. Information was gathered using a systematically designed questionnaire. RESEARCH DESIGN: This study …
Published in Journal of Nursing Science & Practice · Vol. 14, Issue 1, 2024 · pp. 45–50 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