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372 articles for “Diagnostics”
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Modern Chemistry & Chemical Technology in Sensor Formation
Abstract: The field of sensor formation stands at the vibrant intersection of modern chemistry and chemical technology, driven by an insatiable demand for precise, rapid, and sensitive detection across myriad applications. This paper explores the foundational and transformative role these disciplines play in engineering next-generation sensing platforms. Modern chemistry, through its atomic-level precision in synthesizing novel responsive materials – ranging from advanced polymers and supramolecular architectures to cutting-edge nanomaterials like graphene, …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 17, Issue 1, 2026 · pp. 1–9 Read article
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An Analytical Study on Learning Difficulties in Estimation Theory Among Undergraduate Engineering Students
Abstract: Estimation Theory is a critical mathematical foundation for all engineering disciplines, enabling learners to model uncertainty, analyse signals, and derive optimal estimators. However, undergraduate students frequently struggle with its abstract properties, complex derivations, and prerequisite statistical concepts. This study investigates the key learning difficulties faced by students across multiple engineering branches using diagnostic tests, structured questionnaires, and interviews. The findings reveal that students commonly experience challenges related to weak probability …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 Read article
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Depression Detection Using AI with Chatbot Support
Abstract: Depression is a major global health concern and a significant contributor to suicide rates worldwide. India reports a high number of suicide cases, making the early detection of mental distress and depression essential for timely intervention. This research presents an AI-based system for depression detection that integrates deep learning, natural language processing (NLP), and a chatbot for user support. The system analyzes facial expressions using convolutional neural networks (CNNs) and …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 1, 2025 · pp. 01–08 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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Image-Based Crack Morphology Characterisation for Electrical Failure Analysis in Conductive Polymer Composites
Abstract: Electrical performance in conductive polymer composites is strongly governed by crack-network evolution, yet failure analysis typically relies on qualitative image inspection or electrical anomaly detection in isolation. This work proposes an end-to-end framework that converts optical/SEM crack imagery into a standardised crack morphology signature and quantitatively links it to electrical degradation indicators. A two-stage learning strategy is adopted: crack-representation pretraining using the public Concrete Crack Images for Classification dataset, followed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1375-1386 Read article
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Modern Approaches in Lung Cancer Management from Herbal Nanomedicine to Artificial Intelligence
Abstract: Lung cancer continues to be a major global health concern and one of the leading causes of cancer-related mortality worldwide. Despite significant advancements in therapy, there is still a pressing need for safer and more effective therapeutic alternatives; problems such drug resistance, side effects, metastasis, and recurrence continue to impact patient outcomes and quality of life. Examining current advancements in the use of herbal drug-loaded nanoparticles as a novel approach …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 2, 2026 Read article
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Fundamental Principles of Fluid Behavior and Emerging Trends in Modern Fluid Mechanics Research
Abstract: Fluid behavior forms the foundation of numerous engineering technology and scientific applications, including aerospace flows, energy systems, and environmental processes. This paper presents a comprehensive overview of the fundamental principles governing fluid behavior, with a strong emphasis on their relevance to recent trends in fluid mechanic’s research. Core concepts such as fluid statics, fluid dynamics, and conservation laws are discussed to establish a solid theoretical framework. The study further examines …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 1, 2026 · pp. 14–21 Read article
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Structure–Property Modeling of Cement-Based Multi-Component Composites Using Ensemble Machine Learning and Explainable Feature Attribution
Abstract: Accurate prediction of compressive strength is central to structure–property optimization, quality control, and sustainability-driven design in cement-based composite materials. Cementitious systems represent heterogeneous multi-phase composites composed of reactive binder matrices and dispersed aggregate phases, whose macroscopic mechanical performance emerges from complex nonlinear interactions among constituents and curing-dependent microstructural evolution. This study develops a data-driven structure–property modeling framework to quantify the nonlinear dependence of compressive strength on multi-component composite composition and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 112–131 Read article
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Cyber-Secure IoT Framework for Monitoring Fiber-Reinforced Polymer Composites Using Embedded Sensors
Abstract: The present research paper suggests a cyber-safe Internet of Things system in real-time monitoring of fiber-reinforced polymer composites with inbuilt sensors. It is aimed at enhancing structural health maintenance, using sensual, intelligent analysis, and data protection in the same platform. Multi-layer architecture An embedded sensor, signal processing, anomaly detection and lightweight layer of cyber-security are developed. Experimental validation is done under controlled conditions and the performance is measured by these …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 434–458 Read article
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A Study on the Use of AI and Sensors in Aerospace
Abstract: The synergistic combination of modern sensors including artificial intelligence (AI) has significantly changed the aeronautics industry's ongoing quest for increased safety, efficiency, and autonomy. The examination of the critical role these technologies play throughout the whole aerospace lifecycle from design and production to flight operations and maintenance is examined in this research. The eyes and ears of contemporary aircraft, sensors give an unparalleled amount and quality of real-time data about …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 Read article
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Ayurvedic Management of Vātadhika Vātarakta – A Case Series
Abstract: Vātarakta is a classical disorder described in Ayurveda that arises due to the simultaneous vitiation of Vāta and Rakta, resulting in a pathological condition characterized by mutual obstruction (Āvaraṇa) between these two factors. This complex interaction between Vāta and Rakta leads to a wide spectrum of clinical manifestations, making the condition challenging to diagnose and manage effectively. Among the four types of Vātarakta described in classical texts, Vātādhika Vātarakta predominantly …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 Read article
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Post Covid-Sequela: Novel-Inception of DM: A Review
Abstract: As patients recovers from COVID 19 pandemic, a subset of the covid patients experienced a post covid condition with long term symptoms, few weeks after their discharge or recovery from the (SARS-CoV-2) infection. Hence, we tried to prove the hypothesis whether diabetes mellites is an afresh possible sequala of covid infection by systematically evaluating the consistently changing glucose level of the post covid patients. The databases PubMed and Google Scholar …
Published in Research and Reviews : A Journal of Immunology · Vol. 16, Issue 2, 2026 Read article
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Genomic Characterization of Emerging Arboviruses in Rural India
Abstract: Arboviruses (arthropod-borne viruses) represent a rapidly evolving group of pathogens responsible for significant morbidity and mortality, particularly in tropical and subtropical regions. Rural India, characterized by dense vector populations, changing ecological patterns, and limited healthcare infrastructure, has become a hotspot for the emergence and re-emergence of arboviral diseases such as dengue, chikungunya, Japanese encephalitis, and more recently, Zika virus infections. Advances in genomic technologies, including next-generation sequencing (NGS), metagenomics, and …
Published in International Journal of Pathogens · Vol. 3, Issue 2, 2026 · pp. 1–8 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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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
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Infectious illnesses in areas of violence and among refugees
Abstract: Infectious illnesses are a huge and ongoing hazard in conflict zones and among refugee populations. This is because frail health systems, population relocation, and poor living conditions all come together to make transmission risks higher. Armed conflict undermines vital public health infrastructure, such as vaccination programs, disease surveillance, water and sanitation systems, and access to medical care, resulting in the resurgence and proliferation of avoidable and treatable illnesses. Refugee camps …
Published in International Journal of Tropical Medicines · Vol. 3, Issue 1, 2026 · pp. 36–40 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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Non-Small Cell Lung Cancer: Types, Pathogenesis, Diagnosis, and Novel Therapeutic Strategies
Abstract: Non-small cell lung cancer (NSCLC) is the most prevalent type of lung cancer, accounting for over 85% of all cases globally. It remains one of the primary causes of cancer-related death due to its rapid progression, few early symptoms, and late detection. The three main forms of non-small cell lung cancer (NSCLC) are adenocarcinoma, squamous cell carcinoma, and giant cell carcinoma; each has a unique histology, prognosis, and response to …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 2, 2026 Read article
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IoT-Based Battery Health Monitoring for Electric Vehicles Using Machine Learning
Abstract: With increasing utilization of the Electric Vehicles (EV)s in global scale, battery health management becomes a critical factor which has great impact on vehicle performance, safety and longevity. Battery materials, such as NMC LFP lithium-ion batteries and lithium-ion batteries, degrade over time from charging behaviour, heat stress, discharging voltage profiles and environmental limits. Conventional BMS only offer threshold based health diagnostics and cannot perform accurate degradation prediction. This work presents …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 Read article
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Phosphorescence of Carbon Nanodots – The Phenomena and the Applications
Abstract: Photoluminescence has emerged as a fundamental phenomenon in modern biomedical science, enabling advanced diagnostic, therapeutic, and theranostic applications through light–matter interactions at the nanoscale. The ability of photoluminescent materials to absorb electromagnetic radiation and emit light at distinct wavelengths has been widely exploited in bioimaging, biosensing, drug delivery tracking, and photodynamic therapy. Among various photoluminescent nanomaterials, carbon nanodots have attracted significant attention due to their strong emission intensity, tunable fluorescence, …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 4, Issue 1, 2026 · pp. 01–05 Read article