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264 articles for “clinical applications”
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Screening of Pharmaceutically Significant Methioninase-Producing Fungi from the Satpura Range of Hoshangabad District and Its Large-Scale Production
Abstract: L-methioninase, an enzyme with notable anticancer properties, has emerged as a promising therapeutic agent due to its ability to selectively degrade methionine, a critical amino acid for the survival of methionine-dependent cancer cells. Methionine dependency, observed in many tumor cells, is a metabolic vulnerability that can be exploited for targeted cancer therapy. The Satpura Range in the Narmadapuram District, India, with its diverse microbial ecosystems, offers a rich reservoir for …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 2, 2025 · pp. 33–43 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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Scaling of Machine Learning Techniques in Medical Imagining and Biomedical Applications Concerning Healthcare
Abstract: Machine learning refers to a field within computer science enabling computers to learn without explicit programming. Stemming from artificial intelligence's study of pattern recognition and computational learning theory, machine learning develops algorithms capable of learning from vast datasets and making predictions. Its applications span diverse computing tasks like email filtering, network intrusion detection, optical character recognition, and computer vision, where conventional algorithm design proves challenging. Notably, in computer vision, a …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 41–44 Read article
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A Comprehensive Review of Forensic Medicine: Its Evolution, Scope, Applications, and Future Directions
Abstract: Forensic medicine, a key junction of medical and law, has evolved substantially throughout the centuries, responding to scientific and technological advances. Forensic medicine, derived from the Latin term forensis, meaning “before the forum,” has evolved significantly over the centuries from rudimentary methods of determining the cause of death to a sophisticated and highly specialized medical discipline. Today, it encompasses a wide range of fields, including clinical forensic medicine, forensic pathology, …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 18–28 Read article
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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Role of Artificial Intelligence in Simulation and Therapeutics in Neurodegenerative Diseases
Abstract: Neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, etc., are a cause of significant mortality rates due to a lack of curative treatments and their complex nature. Traditional therapeutic methodologies have several disadvantages such as slow diagnosis and a lack of effective treatments. They mainly focused on the management of the disease rather than curing it. The integration of artificial intelligence in the simulation and therapeutics of neurodegenerative …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 19–29 Read article
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The Role of Bioinformatics in Nursing: Transforming Healthcare through Data-Driven Insights
Abstract: Bioinformatics, an interdisciplinary field combining biology, computer science, and information technology, is increasingly shaping the nursing profession. It offers powerful tools for improving patient care, advancing clinical research, and enabling personalized healthcare through data-driven decision-making. This article examines the integration of bioinformatics into nursing practice, tracing its historical roots from the Human Genome Project to its current applications in genomic medicine, precision healthcare, and population health. Nurses now play a …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 18–21 Read article
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Clinical Profile of Dengue Patients who had a Prior Infection with the Covid 19 Virus in a Tertiary Care Centre
Abstract: This cross-sectional analytical study conducted in a tertiary care center aims to investigate the clinical profile of Dengue virus-infected patients with a prior history of COVID-19 within the last three years. Dengue, a prevalent tropical disease, ranges from mild fever to severe conditions like hemorrhagic fever and shock syndrome. The study utilizes the World Health Organization's 2009 classification for Dengue and delineates the febrile, critical, and recovery phases of infection. …
Published in Recent Trends in Infectious Diseases · Vol. 1, Issue 1, 2024 · pp. 34–38 Read article
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Beyond Generalized Treatment: The Future is Personalized Medicine
Abstract: Personalized medicine, which is also called as precision medicine, is reestablishing the view of new healthcare by replacing the traditional "one-size-fits-all" approach with individual therapies made according to a patients unique genomic organization, environment, and lifestyle. This article talks about the scientific foundation, important applications, ethical challenges, and the significant potential of personalized medicine in enhancing the clinical outcomes. From oncogenic and genetic disorders to chronic diseases, the addition of …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 2, 2025 Read article
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Emerging Digital Trends in Virology Software: Optimizing Viral Discovery, Surveillance,and Patient Management.
Abstract: Virology and antiviral therapeutics are being reshaped by rapid advances in computational tools, automation platforms, and virus-focused digital health applications. Software systems now span the entire virology value chain, from in silico viral target identification and antigen design, to AI-supported clinical trial management for vaccines and antivirals, to post-marketing pharmacovigilance and patient-facing mobile tools. This review examines current and emerging software trends relevant to virus studies, emphasizing applications in viral …
Published in International Journal of Virus Studies · Vol. 3, Issue 1, 2026 · pp. 29–38 Read article
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Graphene Based Electronic Skin for Wearable Health Monitoring and Human– review on Machine Interaction, Materials, Structures and AI Integration
Abstract: Graphene-based electronic skin (e-skin) has emerged as a transformative technology for next-generation wearable health monitoring and advanced human–machine interaction (HMI). Owing to its outstanding electrical conductivity, mechanical flexibility, atomic-scale thickness, and biocompatibility, graphene enables the fabrication of ultrathin, conformal, and multifunctional sensors capable of mimicking the sensory functions of natural human skin. Over the past decade, research in this domain has progressed rapidly across four interconnected fronts: material synthesis and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Artificial Intelligence for Improved Healthcare: A Case Study and Applications
Abstract: Artificial intelligence (AI) in healthcare ushers in a revolutionary period of innovation, but it also brings with it significant ethical dilemmas. This paper explores the complex relationship between AI and healthcare, emphasizing both its useful applications and the moral conundrums that arise. Ethical issues span a wide range, including patient privacy, transparency, accountability, and the unintentional reinforcement of biases in AI algorithms. Privacy concerns take center stage as healthcare providers …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 1–12 Read article
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Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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Mass Spectrometry–Based Phosphoproteomic Markers to Predict Kinase Inhibitor Response in Solid Tumors
Abstract: Mass spectrometry-based phosphoproteomics has emerged as a powerful tool for predicting kinase inhibitor responses in solid tumors, offering direct functional insights into signaling pathways that surpass traditional genomic profiling by capturing dynamic kinase activities and adaptive resistance mechanisms. Technological breakthroughs, including data- independent acquisition (DIA), trapped ion mobility spectrometry (timsTOF), and efficient enrichment methods like TiO2 or IMAC, now enable comprehensive profiling of over 40,000 phosphorylation sites from limited clinical …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 2, 2026 Read article
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Integrating Ayurveda in Infertility Management: A Case Study on Fimbrial Blockage
Abstract: Infertility significantly impacts a woman’s psychological and physical health, as well as that of her family. Fallopian tube blockage is one of the leading causes of female infertility, accounting for a substantial number of cases globally. Conventional medical approaches, including in vitro fertilization (IVF) and surgical procedures, often present barriers due to their high cost, invasive nature, and limited accessibility. Additionally, cultural, financial, and personal considerations can further restrict their …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 12, Issue 3, 2025 · pp. 12–19 Read article
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Medicinal Properties of Oxytenanthera abyssinica: A Narrative Review
Abstract: Oxytenanthera abyssinica, a plant local to the African landmass, has gotten a parcel of intrigued in later a long time for its conceivable restorative benefits; it has been utilized in conventional medication for decades since of its assumed mending capabilities. In spite of its long history, careful logical examination into its restorative potential is being attempted. This review paper explore into the multidimensional part of O. Abyssinica is in progressed …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 13, Issue 2, 2026 Read article
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Unlocking Potential: Capecitabine’s Evolution as an Anticancer Wonder Drug
Abstract: Capecitabine, a precursor to 5-fluorouracil (5-FU), is Anticancer Drug in treating solid tumors like colorectal, breast, and gastric cancers. Its mechanism involves converting to 5-FU mainly within tumor cells, reducing toxicity while maximizing effectiveness. Besides being effective alone, it is also valuable in combination therapies, showcasing its versatility in cancer treatment. This review explores the transformative journey of capecitabine as a pivotal anticancer drug. Beginning with an introduction to its …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 11, Issue 2, 2024 · pp. 17–24 Read article
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Pain Management Through Ayurvedic Tablets and Capsules
Abstract: Triphala Guggulu is a classical formulation widely used in Ayurveda for the management of metabolic and inflammatory disorders. It represents a synergistic combination of Triphala – composed of Emblica officinalis, Terminalia bellirica, and Terminalia chebula – along with the oleo-gum resin of Commiphora mukul. In traditional Ayurvedic practice, this formulation has been prescribed for conditions, such as arthritis, obesity, hyperlipidemia, and chronic constipation, primarily due to its reputed ability to …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 13, Issue 1, 2026 · pp. 23–28 Read article
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Synthesis, Characterization of New Imidazolidin-4-One Containing Azo Compound Derived from Acetylacetone as Antibacterial and Antioxidant Agents
Abstract: In the present study, new derivatives of imidazolidine-4-one was prepared. Which involved reactions to diazonium salt of o-methoxy aniline with acetylacetone in the presence of sodium hydroxide, and isolating the azo compound as a brown precipitate. The azo diketone reacts efficiently with aromatic amine derivatives to produce Schiff bases as a light yellow and dark brown precipitates, and from this Schiff bases three derivatives of imidazolidine-4-one was prepared by reacting …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 17, Issue 1, 2026 · pp. 94–114 Read article
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Dual-Stream Deep Learning Framework for Brain CT Image Classification and Implications for Polymer Composite Neuro Implant Evaluation
Abstract: Early and accurate classification of brain CT images is critical for diagnosing conditions such as aneurysms, tumors, and related lesions. We present a dual-stream image-classification framework that fuses convolutional neural network (CNN) features with handcrafted Histogram of Oriented Gradients (HOG) descriptors to jointly capture global semantics and local textural cues. The pipeline begins with modality unification via pixel-wise averaging to form a fused input, which is then processed in parallel …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 172–179 Read article