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163 articles for “Diagnostic Methods”
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Early Autism Diagnosis: Machine Learning Models and Their Effectiveness
Abstract: Diagnosis is of utmost importance for timely intervention and support. However, traditional diagnosis methods, which are based on subjective assessment, are delayed. This project explores the role that machine learning techniques might play in enhancing the accuracy and effectiveness of ASD detection. Several state-of-the-art classification algorithms were benchmarked using a dataset from Kaggle. Logistic Regression, XG Boost, Random Forest, Decision Tree, and Gradient Boosting were taken into consideration. Other performance …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
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An Overview on AI-Driven IoT Based Decision Making in Climate change Study: KSK approach in Climate Change Study
Abstract: As the Earth’s climate enters a state of unprecedented volatility, the traditional methods of ecological observation—characterized by delayed reporting and fragmented data—are no longer sufficient. This study investigates the paradigm shift toward AI-driven IoT (KSK Approach)-based decision-making frameworks as the primary frontier in climate science. By deploying a "planetary nervous system" of interconnected sensors—measuring everything from soil moisture in the Sahel to glacial melt rates in the Arctic—we generate a …
Published in International Journal of Climate Conditions · Vol. 3, Issue 1, 2026 · pp. 1–10 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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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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Designing Aspects and Recent Advances in Digital Holographic Microscopy
Abstract: Recent advances in Digital Holographic Microscopy have been discussed in this paper, besides throwing some light on the designing aspects of optical components like beam splitter and neutral density filter for the optimization of system performance. Some important related subtopics like spectral resolution of digital holograms, and Fourier-synthesis holography have been technically discussed. The optimization of acoustical holographic components for use in renewable energy production is presented in this study. …
Published in Research & Reviews : Journal of Physics · Vol. 14, Issue 2, 2025 · pp. 06–18 Read article
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ML-Driven Defect Detection in Additive Manufacturing of Polymer Composites Using Thermal Imaging
Abstract: Polymer-based flexible biosensors have emerged as a pivotal technology in continuous health monitoring, yet their deployment in real-world settings is often hindered by undetected micro-defects and signal distortion caused during fabrication or usage. Existing diagnostic frameworks typically rely on post-hoc processing or bulky instrumentation, failing to offer scalable, real-time detection during additive manufacturing workflows. This study introduces an end-to-end, thermographic imaging-integrated framework for in-situ defect identification during the additive manufacturing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 201–215 Read article
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Comprehensive Strategies for the Prevention and Management of Genital Thrush in Males and Females: A Public Health Approach in Punjab (September 2024 to February 2025)
Abstract: Background: Genital thrush, a common fungal infection caused mainly by Candida albicans, affected both men and women, leading to itching, discomfort, and recurrent infections. In Punjab, high humidity, poor hygiene awareness, excessive antibiotic use, and limited access to healthcare contributed to its widespread occurrence. Without effective prevention and management strategies, the condition significantly impacted quality of life. Addressing this issue through a public health approach was essential for reducing its …
Published in Research and Reviews: A Journal of Medicine · Vol. 15, Issue 3, 2025 Read article
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Passenger car fuel economy: Insights from big data analytics
Abstract: The increasing availability of real-world vehicle telematics through On-Board Diagnostics II (OBD-II) systems has enabled data-driven evaluation of passenger car fuel economy beyond conventional laboratory-based test cycles. While standardized certification procedures ensure repeatability, they often fail to capture the influence of real-world traffic conditions, driver behaviour, and transient vehicle operation. This study presents a structured Big Data Analytics (BDA) approach for analysing high-frequency OBD-II data collected from a gasoline passenger …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 8–19 Read article
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Impact of Training Program on Recent Innovations in Oncology Among Nursing Professionals
Abstract: Introduction: In recent years, there have been significant advancements and trends in the field of oncology treatment in India. This study aimed to evaluate impact of training program on knowledge regarding recent innovations in oncology among nursing professionals. After ethical approval, a pre-experimental, one group pretest- post-test design was used to conduct this research at anursing college of Punjab. Methods: The sample was selected using the total enumerative sampling technique. …
Published in International Journal of Oncological Nursing and Practices · Vol. 3, Issue 1, 2025 · pp. 9–14 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 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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AI-Driven Predictive Maintenance Framework for Intelligent Vehicle Health Monitoring
Abstract: The accelerated development of smart and connected car systems made the necessity to find the accurate and real-time predictive maintenance solutions which would minimize the number of unexpected failures as well as increase the cars on-road safety. The current paper proposes an artificial intelligence-based hybrid predictive maintenance system that combines Long Short-Memory (LSTM) networks and the XGBoost predictor to provide a potent vehicle fault diagnosis, Remaining Useful Life (RUL) prediction, …
Published in Trends in Machine design · Vol. 13, Issue 1, 2026 · pp. 1–17 Read article
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Optimization of Reaction Parameters for Biodiesel (Methyl Ester) Synthesis Using Surface Response Methodology
Abstract: The Polyoxo vanadate catalytic trans-esterification of waste cooking oil (WCO) was carried out by optimizing four reaction parameters which include: catalyst loading, methanol/oil ratio, temperature, and reaction time. These optimized parameters are 0.5 g, 0.8 g, and 1.2 g catalyst loading, 3:1, 6:1 and 9:1 methanol/oil ratio, 45°C, 60°C and 65°C reaction temperature, 45 min, 60 min and 90 min reaction time. The regression equation in the uncoded units of …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 14, Issue 3, 2024 · pp. 20–28 Read article
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Integrative Perspectives on Lipoma: Traditional Therapeutics from Siddha, Ayurveda, and Unani with Biomedical Correlates
Abstract: Background: Lipoma is the most common benign soft tissue tumor, with an incidence of approximately 2 per 1,000 individuals annually. Modern biomedicine attributes its pathogenesis to genetic abnormalities like HMGA2 rearrangements and dysregulated adipogenesis via PPARγ pathways. Effective pharmacological therapies are lacking. Traditional Indian systems – Siddha, Ayurveda, and Unani – offer unique perspectives and non‑surgical approaches yet remain underexplored in integrative research. Objective: To critically evaluate the descriptions, pathophysiological …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 13, Issue 1, 2026 · pp. 19–33 Read article
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Human Deep Skin Surface Vibration Frequency Detection from CT and DT Signals Using Genetic Algorithms
Abstract: To diagnose respiratory problems early on, a contactless, non-invasive, real-time assessment of human vibration is a crucial prerequisite. Optoelectronic plethysmography (OEP) and the forced oscillation technique (FOT), are two widely utilized methodologies, depending on variations in each patient’s local chest impedance. Calibration of the devices before each measurement is hence the primary problem of these approaches. This report presents a simulation-based analysis to assess the effectiveness of the CT and …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 1, 2024 · pp. 9–16 Read article
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The Role of Helicobacter pylori in Stomach Cancer Incidence: A Study in Rural Communities in Rajasthan
Abstract: Background: Stomach cancer remains a major global health challenge, with a particularly high burden in developing regions. Helicobacter pylori (H. pylori) infection is a known risk factor for gastric malignancy. In India, especially in rural states like Rajasthan, there is limited data on the prevalence of H. pylori and its association with stomach cancer, despite the high incidence of gastric diseases. Methods: This cross-sectional study was conducted among rural communities …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 45–50 Read article
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Role of ABCDE Rule in Wound Assessment
Abstract: The diagnosis of chronic wounds poses an interdisciplinary and interprofessional challenge. In routine clinical practice, the appropriate diagnostic workup is frequently carried out insufficiently. In addition to financial obstacles, those involved in the process often lack the required knowledge, a circumstance that must be overcome. Today, the treatment of patients with chronic wounds is thus, commonly, merely symptomatic and frequently not accompanied by determination of the exact cause. The ABCDE …
Published in Research and Reviews: A Journal of Health Professions · Vol. 14, Issue 3, 2024 Read article
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A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 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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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