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50 articles for “Disease-X”
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Disease X: Unveiling the Unknown Pathogen and Enhancing Global Preparedness
Abstract: “The concept of “Disease X” was introduced to drive the creation and refinement of versatile technologies such as vaccines, therapeutic drugs, and diagnostic tests, which could be swiftly adapted and utilized in response to future infectious disease outbreaks with epidemic or pandemic potential. The aim was to establish a proactive approach to emerging health threats by developing platform technologies capable of addressing a broad spectrum of potential pathogens. The COVID-19 …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 3, 2024 · pp. 15–20 Read article
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Prime Editing and Base Editing in Human Hematopoietic Stem Cells Toward Scarless Correction of Monogenic Blood Disorders
Abstract: Monogenic hematological disorders – such as sickle cell disease (SCD), β-thalassemia, and X-linked chronic granulomatous disease (X-CGD) – affect >400, 000 newborns worldwide each year, with a considerable burden in low-resource settings . Although donor-derived allogeneic hematopoietic stem-cell transplantation (HSCT) is widely regarded as curative, its application is limited due to issues of donor availability and graft-versus-host disease (GVHD) and conditioning-related toxicity. DSB-based conventional CRISPR-Cas9 strategies are limited by inefficient …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 1, 2026 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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DentiDetect: Dental Diagnosis Powered by Deep Learning
Abstract: Dental X-rays play a crucial role in modern dentistry, enabling dentists to detect cavities, bone loss, and other hidden dental issues that are not easily visible during a routine examination. X-rays offer a clear picture of teeth, bones, and nearby tissues, enabling early identification of issues. This helps create more efficient treatment strategies and improves patient outcomes. Three commonly used types of X-rays include bitewing, periapical, and panoramic. Bitewing X-rays …
Published in Research and Reviews: A Journal of Dentistry · Vol. 15, Issue 3, 2024 · pp. 21–26 Read article
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Assessing the Effectiveness of New Fungicides Against Potato Late Blight Disease (Phytophthora Infestans)
Abstract: An experiment was conducted in the field of the Plant Pathology Division, Regional Agricultural Research Station (RARS), Bangladesh Agricultural Research Institute (BARI), Jamalpur, Bangladesh during the rabi season of 2024–2025 to determine the appropriate chemical fungicide for controlling late blight disease of potato. The evaluation included twenty-five new fungicides approved by the Pesticide Technical Advisory Committee (PTAC), Bangladesh, along with a standard control (Ridomil Gold MZ 68 WG) and an …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 28–38 Read article
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AI in Healthcare: Drug Delivery in Tuberculosis
Abstract: Tuberculosis (TB) , mainly caused by Mycobacterium tuberculosis, remains a major global health burden, accounting for millions of new infections and deaths each year. Although progress has been made in diagnosis and treatment, the growing threat of multidrug-resistant (MDR) and extensively drug-resistant (XDR) TB makes disease control increasingly difficult. Conventional diagnostic approaches such as chest X-rays, sputum smear microscopy, and culture methods continue to play an important role, but they …
Published in Trends in Drug Delivery · Vol. 13, Issue 1, 2026 · pp. 9–17 Read article
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An Evaluative Comparison of CD123 and CD66c as Biomarkers to Detect Minimal Residual Disease in B-Cell Acute Lymphoblastic Leukemia
Abstract: Background: B-cell Acute Lymphoblastic Leukemia (B-ALL) often shows lineage heterogeneity with lymphoid cells expressing myeloid markers. Minimal Residual Disease (MRD) refers to the small number of cancer cells that may remain in a patient's body after treatment and that are undetectable by standard diagnostic methods. In diseases like B-cell Acute Lymphoblastic Leukemia (B-ALL), MRD is a critical prognostic indicator, as its presence can signal a higher risk of relapse. In …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 · pp. 7–12 Read article
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Comparative Analysis of Data Augmentation Techniques in CNN-based Classification of Atelectasis
Abstract: This research delves into the critical issue of atelectasis, its causes, and potential complications if left untreated. Leveraging deep learning algorithms, particularly convolutional neural networks (CNN), the paper explores their application in medical image analysis, focusing on the detection of atelectasis using the “chestX-ray8” database. The study compares various data augmentation techniques for improved accuracy, showcasing the importance of augmentation in enhancing model generalization. Through meticulous experimentation and evaluation, the …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 3, 2024 · pp. 1–8 Read article
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Repurposing Liv-52 For Primary Sclerosing Cholangitis: A Computational Docking And Pharmacokinetic Study To Evaluate Its Bile Flow-Regulating Potential
Abstract: Primary Sclerosing Cholangitis (PSC) is a long-term liver disease where the bile ducts become inflamed and scarred over time. This scarring can block the flow of bile, leading to liver damage and, eventually, liver failure. The etiology of PSC remains largely unknown, and current treatment options are limited, highlighting the need for novel therapeutic strategies. This study aims to repurpose Liv-52, a traditional herbal formulation known for its hepatoprotective properties, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 2, 2025 Read article
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A Knowledge Graph Approach for Breast Cancer Diagnosis and Data Sharing Platform Implementation in the Context of Human Papillomavirus Infection
Abstract: Background: Breast cancer remains among the most prevalent malignancies in women worldwide, and effective diagnosis and data integration continue to challenge clinical practice. Diagnostic reports from mammography and ultrasound contain rich clinical information that is often under-utilised due to heterogeneous formats and limited data-sharing infrastructure. In the context of human papillomavirus (HPV) infection, which may influence oncogenic pathways and data complexity, advanced computational methods offer new solutions to this problem. …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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State of the Art: A Pandemic Big HealthCare Analytics Solution: Image Data Classification Using Quantum MAML
Abstract: The modern age is facing many pandemic healthcare problems, e.g., covid 19, infections, inflammations, and many more, leading to critical, deadly situations. Survival rate can be increased with proper diagnosis of such data. We have proposed one of the implementations based on a medical image dataset for classification using deep reinforcement learning (RL) with quantum computing. Deep RL is the combination of DL (deep learning), generative adversarial network (GAN), and …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 1–9 Read article
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Detection of Pneumonia in COVID-19 Patients Using X-ray Images
Abstract: This study explores the use of chest X-ray image analysis and deep learning methods to identify pneumonia in COVID-19 patients. Due to the pandemic, Proper as well as immediate examination of COVID-19 is now essential for patient care and disease control. This study proposes a novel approach that uses convolutional neural networks (CNNs) to automatically predict pneumonia in COVID-19 patients using chest X-ray images. In this study, an X-ray of …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 13–23 Read article
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Magnetic ZnxFe2–xO3 Nanoparticles Enhanced Nanobiosensor Integrated with MOSFETs for Efficient Detections of Biomolecules and Cancerous Cells
Abstract: The human brain is mostly responsible for intelligence and consciousness. An artificial equivalence of this action is nanobiosensor, which is used in artificial intelligence. The need for nanodiagnostics platforms for detecting diseases at the genetic, molecular, and cellular level has triggered the development of nanobiosensors integrated with MOSFETs. This device enables simple, inexpensive rapid tests, accurate imaging methods, and accurate molecular diagnosis at point-of-care (POC). This device is seen as …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 14, Issue 3, 2024 · pp. 33–44 Read article
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Explainable Machine Learning Integrated with Polymer-Based Diagnostic Technologies for Liver Health Classification
Abstract: Early and reliable assessment of liver health is essential for timely treatment, yet most machine-learning approaches face limitations such as class imbalance and low clinical interpretability. This study proposes a polymer-integrated, explainable machine-learning framework that combines SMOTE-based data balancing, Logistic Regression, and XAI techniques (SHAP and LIME) for transparent liver-health classification. In addition to ML modelling, the study emphasizes the emerging role of polymer-based biosensors, microfluidic polymer chips, polymer nanomaterials, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 631–643 Read article
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Advancements in AI-Driven Diagnostics for Dental Health: A Comprehensive Review
Abstract: Dental diseases, also known as oral diseases or dental conditions, encompass a range of health problems affecting the teeth, gums, mouth, and associated structures. These conditions can lead to pain, discomfort, and severe complications if left untreated. Early detection and accurate diagnosis are crucial for effective treatment and prevention of further complications. This comprehensive literature review aims to identify common dental problems such as Tooth Decay (Cavities), Gingivitis, Periodontitis, and …
Published in Current Trends in Signal Processing · Vol. 14, Issue 2, 2024 · pp. 1–7 Read article
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Deep Learning -Based Dental Issue Detection
Abstract: Dentistry is vital for preserving oral health, a key component of overall wellness. Early identification of dental issues is crucial for effective treatment and avoiding further complications. Conventional approaches to diagnosing dental problems typically depend on physical examinations and visual assessments by skilled professionals, which can be both time-intensive and influenced by individual judgment.In recent years, the application of deep learning algorithms has demonstrated significant potential in automating and enhancing …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 1, 2025 · pp. 18–23 Read article
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Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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Artificial Intelligence in Drug Repurposing: A Short Impact Assessment
Abstract: Artificial intelligence (AI) in pharmaceutical repurposing has become a game-changing tool that opens new avenues for the application of new drugs that have already been approved. Traditional drug discovery is a lengthy and expensive process, whereas AI can rapidly analyze vast datasets of biological, chemical, and clinical information to predict drug-disease interactions. AI-driven techniques, such as machine learning, natural language processing, and deep learning, enable the identification of potential repurposing …
Published in Trends in Drug Delivery · Vol. 11, Issue 3, 2024 · pp. 42–45 Read article
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A Lightweight Cost-Sensitive Explainable Ensemble Framework for Early Heart Disease Risk Prediction
Abstract: Cardiovascular disease is still one of the leading causes of death, and hence, the early prediction of risk is a very important task in preventive medicine. Although recent studies have shown encouraging results in the application of machine learning algorithms to the prediction of heart disease, it has been noticed that most of the algorithms are more concerned with accuracy-driven optimization than the concerns of safety and false negatives. In …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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X-Ray Insight: Deep Learning-Enhanced Detection and Grading of Knee Osteoarthritis
Abstract: Osteoarthritis (OA) is the most prevalent form of arthritis affecting the knee. It is a degenerative joint disease characterized by the gradual deterioration of cartilage, typically impacting individuals aged 50 and above, although it can also occur in younger people. The condition progresses slowly, with symptoms intensifying over time, leading to significant pain and discomfort. Early diagnosis and intervention can significantly alleviate pain and enhance the quality of life for …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 2, Issue 2, 2024 · pp. 1–6 Read article