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62 articles for “AI-based Disease Identification”
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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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Molecular Pharmacokinetics and Structural Docking of Phenolic Acids for Targeting NF-κB Pathway Components in Inflammation and Fibrosis: A Computational Approach Toward Therapeutic Discovery
Abstract: Inflammation and Fibrosis are critical pathological processes associated with various chronic diseases, often mediated by the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling pathway. This study investigates the therapeutic potential of phenolic acids as modulators of the NF-κB pathway, aiming to identify novel ligands that can effectively interact with key components of this signaling cascade. A comprehensive computational approach was employed, utilizing molecular docking, pharmacological screening, and post-docking …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 3, Issue 1, 2025 · pp. 14–31 Read article
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Viral Chronicles: The Ever-Evolving Saga of COVID-19
Abstract: Coronaviruses, belonging to the family of RNA viruses, have recently captured global attention owing to their remarkable ability to infect a diverse array of species, ranging from animals to humans. These viral agents, recognized by their characteristic crown-like morphology when observed through electron microscopy, have a historical association with zoonotic diseases. Previous examples include Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) and Middle East Respiratory Syndrome Coronavirus (MERS-CoV). The term "Corona" …
Published in International Journal of Virus Studies · Vol. 1, Issue 1, 2024 · pp. 16–25 Read article
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Revolutionizing Vaccine Development:The Transformative Role of Bioinformatics in Designing Next-Generation Immunotherapies
Abstract: Vaccines have long been central to the prevention and control of infectious diseases, dramatically reducing morbidity and mortality worldwide. In the modern era, the integration of bioinformatics has revolutionized vaccine development by enabling rapid, precise, and cost-effective identification of potential vaccine targets. This seminar explores the multifaceted applications of bioinformatics in vaccinology, including antigen discovery, epitope prediction, structural modeling, molecular docking, and immunoinformatics-driven vaccine design. Special emphasis is placed on …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 19–33 Read article
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ML Analysis of Factors Affecting Vaccination in Rural Children: A Machine Learning Approach
Abstract: Vaccination remains one of the most effective public health interventions for preventing childhood diseases, yet rural regions in India continue to experience uneven immunization coverage due to multiple socioeconomic and geographic barriers. This research applies machine learning techniques to identify and analyze the major determinants influencing childhood vaccination uptake in rural communities. The study utilizes survey-based demographic, socioeconomic, and healthcare-related parameters to build predictive models that classify children as vaccinated …
Published in International Journal of Vaccines · Vol. 3, Issue 2, 2026 Read article
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Nutraceuticals Unveiled: Exploring the Science, Benefits, and Future of Functional Food
Abstract: The rapidly developing subject of nutraceuticals is critically examined in this review, with a focus on its scientific basis, proven health advantages, and possible future applications in the functional food industry. Key bioactive ingredients that contribute to the therapeutics effectiveness of functional foods, including flavonoids, polyphenols, carotenoids, probiotics, and essential fatty acids, have been identified and characterized as a result of recent developments in nutritional science. Both experimental and clinical …
Published in International Journal of Nutritions · Vol. 2, Issue 2, 2025 Read article
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AI-Based Preventive Healthcare Using Quantum Computing
Abstract: With its improved performance and capabilities, quantum machine learning (QML) is becoming a promising field, especially in the healthcare industry for tasks like early heart disease prediction. In this work, a Quantum Support Vector Classifier (QSVC) is proposed as the basic classifier for a bagging ensemble learning model. Shapley Additive explanations (SHAP) are used to evaluate the significance of each attribute in the predictions in order to improve explainability. Using …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 2, 2025 Read article
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The Role of Artificial Intelligence and Machine Learning in Redefining Global Healthcare Systems and Advancing Medical Innovation
Abstract: Health Services are being revolutionized with AI and ML through improved accuracy, efficiency and accessibility in the delivery of health care. With AI and ML, it is now possible for health care professionals to assess varying amounts of complex clinical data in a relatively short amount of time, therefore, creating opportunities for early detection of disease, increasing the odds of accurate diagnosis, and improving the ability to make informed clinical …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 14–19 Read article
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IoT-based Heart Attack Prediction System Using Machine Learning
Abstract: Heart disease, particularly heart attacks, is one of the leading causes of mortality worldwide. Timely detection and prompt intervention play a vital role in significantly improving the survival rates of individuals at risk of cardiac events. Unfortunately, most traditional healthcare systems are not equipped with mechanisms for continuous, real-time monitoring of patients' cardiovascular health. This limitation makes it extremely difficult for healthcare providers to identify warning signs early enough to …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 2, 2025 · pp. 1–5 Read article
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A summary continuation analysis evaluating the prevalence and predictors of diabetic retinopathy in newly diagnosed type 2 diabetic patients.
Abstract: Context: Diabetic retinopathy (DR), the leading cause of acquired blindness in adults, affects approximately 93 million people globally. It is a serious complication of type 2 diabetes, resulting from prolonged damage to the blood vessels in the retina. Although largely preventable and treatable, DR continues to be the main cause of vision loss among working-age adults and significantly impacts quality of life. While most studies on DR in Nepal have …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 21–30 Read article
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Exploring Potential Phytochemicals for Myasthenia Gravis Treatment: A Molecular Docking and ADME Analysis Approach
Abstract: Objective: Muscle feebleness and exhaustion derived from a disruption in neuromuscular transference are hallmarks of the crippling autoimmune disease myasthenia gravis (MG). The drawbacks of the current MG therapy options are frequently partial efficacy and adverse effects. To investigate the potential of phytochemicals in MG control, in this work we integrated molecular docking with ADME (absorption, distribution, metabolism, and excretion) analysis using a computer method. We identified molecules exhibiting favorable …
Published in International Journal of Molecular Biotechnological Research · Vol. 2, Issue 2, 2024 · pp. 1–13 Read article
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AI-Enabled Linear Regression Model for Spectroscopic Milk Adulteration Analysis
Abstract: Milk adulteration poses a serious threat to public health and quality assurance in the dairy industry. This requiring rapid, reliable, and non-destructive detection techniques. This study presents a linear regression-based analytical model for identifying and quantifying milk adulteration using spectroscopic data. Spectral measurements of milk samples, including both pure and adulterated variants were acquired using spectroscopic techniques at relevant wavelengths.Blending of other components in pure milk , is specifically called …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 15, Issue 1, 2026 · pp. 28–42 Read article
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Computer-aided Drug Design Method for Anti-hepatitis C Drug Design
Abstract: Hepatitis C is a disease caused by the hepatitis C virus and can cause serious liver damage. There is currently no vaccine for this disease and the number of infections continues to increase worldwide. Currently used antiviral drugs are interferon alfa-2a and ribavirin, but about half of patients do not respond to therapy. Therefore, new drugs that protect against hepatitis C need to be investigated. Computational drug methods have been …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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CNN-Based Diagnosis of Skin Cancer from Dermoscopic Images
Abstract: Skin cancer has become one of the diseases widely spread over the globe, with melanoma becoming a severe threat to one’s health. Detection of such diseases at the initial stage saves an individual from drastic damage. Using a Convolutional Neural Network (CNN) for detecting skin cancer through image classification as benign or malignant provides significant support to dermatological practice and reduces dependence solely on subjective visual examination. Dermatologists often face …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 1, 2026 · pp. 37–42 Read article
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Deep Learning based Solution for Leaf disease Detection in Crops and Fertilizer Recommendation
Abstract: The field of agriculture faces significant threats, including diseases that attack plant leaves. To address this issue, our system assists farmers in promptly detecting plant diseases using advanced technology. The user, typically a farmer, only needs to capture an image of the affected leaf and input it into our system. Our system then analyzes the uploaded image to accurately identify the specific disease afflicting the leaf. This analytical process is …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 31–40 Read article
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GreenDiagnosis: Intelligent Crop Disease Detection Using Deep Learning Algorithm
Abstract: Agriculture in parts of India relies on labour-intensive traditions, maintaining disease-free crops is crucial. Manual methods can be inaccurate, driving farmers towards AI-based solutions. AI offers a proactive approach to address real-time farming challenges. Among these is the invasion of pests, which diminishes crop quality. Combating pest-related diseases poses a challenge, prompting innovation. Effective surveillance and early detection of crop diseases play a pivotal role in ensuring global food security …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 8–18 Read article
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Advancing Gene Therapy: Next-Generation Viral Vector Engineering for Precision, Safety, and Scalability
Abstract: Gene therapy has emerged as a paradigm-shifting modality for the treatment of genetic disorders, malignancies, and rare diseases through the delivery of therapeutic nucleic acids aimed at correcting or modulating dysfunctional gene expression. Among the various delivery systems, viral vectors including adeno-associated viruses (AAVs), lentiviruses, adenoviruses, retroviruses, and herpes simplex viruses have proven indispensable owing to their high transduction efficiencies and adaptability. This review offers a comprehensive assessment of viral …
Published in International Journal of Virus Studies · Vol. 2, Issue 2, 2025 · pp. 37–55 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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Nanoparticle-Based Early Diagnostic Tools for Tuberculosis and Malaria in Rural India
Abstract: Malaria and Tuberculosis continue to be two major public health challenges in rural India. The interplay between an inefficient health care system, late diagnosis, and under-identification of cases contributes to the high morbidity and mortality associated with TB and Malaria. Conventional methods, such as sputum microscopy for TB, microscopy and rapid diagnostic tests (RDTs) for malaria, have a higher benchmark of sensitivity that requires a certain amount of time, skilled …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 45–51 Read article
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Identification of Secondary Metabolites from Zingiber officinale as Inhibitors for Keap 1-Nrf2 small Molecules through Molecular Docking Techniques
Abstract: Objective: Therapeutic plants aid in treating cancer-based cell signaling pathways and preventing certain risk factors. Zingiber officinale has a variety of anti-inflammatory characteristics also contributing to enhanced immunity, reducing cancer risk and used to target the KEAP NRF2. When overexpressed in response to oxidative stress and DNA damage, elevates the risk of developing multiple cancers. NRF2 cellular sensors, which also control and coordinate their expression aid in defending healthy cells …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 1, Issue 2, 2023 · pp. 35–48 Read article