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All Journal Journal of Current Health Sciences Journal of Tropical Pharmacy and Chemistry
Mahedi, Rezwan Ahmed
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Biochemistry, Genetics & Molecular Biology Chemistry Dentistry Health Professions Immunology & microbiology Medicine & Pharmacology Neuroscience Nursing Public Health Veterinary

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Current Trends and Future Prospects of Artificial Intelligence in Transforming Radiology Mahedi, Rezwan Ahmed; Iqbal, Hrishik; Azmee, Raiyan; Azmee, Marzan; Jakir, Fatiha; Nishan, Mufassir Ahmad; Uddin, Mohammed Burhan; Afrin, Sadia
Journal of Current Health Sciences Vol. 4 No. 2: November 2024
Publisher : Utan Kayu Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47679/jchs.202487

Abstract

Artificial intelligence (AI) has rapidly transformed numerous industries, including medicine, with radiography standing to benefit significantly from its capabilities. AI enhances diagnostic accuracy, reduces errors, and improves patient care by leveraging large datasets from digital radiographs commonly used in medical and dental practices. Despite these advantages, the impact of AI on image acquisition and radiographer workflows remains underexplored in radiography literature. This review aims to evaluate the effects of AI on radiographic practices, address regulatory challenges, and explore its integration into educational frameworks for radiologists and radiographers. It highlights AI's role in automating tasks, enhancing diagnostic precision, and improving clinical decision-making. A systematic literature search was conducted using PubMed and Google Scholar up to December 2024, with terms including "artificial intelligence," "machine learning," "deep learning," "radiography," and "diagnostic imaging." Seventy-seven peer-reviewed articles and conference papers focusing on AI applications in digital dental radiography were analyzed to extract data on AI methodologies and their potential applications. The findings reveal that AI-powered solutions enhance efficiency in complex imaging tasks, such as lesion identification and triage in mammography, and real-time assessments in cross-sectional imaging, reducing the need for re-scans and increasing patient throughput. However, widespread adoption faces obstacles related to ethical and legal concerns, including data privacy, algorithmic bias, and the need for transparency. While AI demonstrates significant potential to automate workflows, improve diagnostic accuracy, and optimize patient care in radiography, challenges related to human oversight, professional adaptation, and regulatory compliance must be addressed. Further research is needed to fully understand AI’s impact on radiography and to maximize its clinical utility.
Investigation of Total Tannin, Phenolic & Flavonoid Content of Araucaria Heterophylla for Antioxidant Source Ghosh, Ankita; Paul, Shimanta; Ghosh, Susmita; Akter, Sadia; Mahedi, Rezwan Ahmed; Afrin, Sadia; Hasan, Akayed; Hasan, Ali Mohamod Wasaf; Sayeed, Md Abu; Syrmos, Nikolaos
Journal of Tropical Pharmacy and Chemistry Vol. 8 No. 2 (2024): J. Trop. Pharm. Chem.
Publisher : Faculty of Pharmacy, Universitas Mulawarman, Samarinda, Indonesia, 75117, Gedung Administrasi Fakultas Farmasi Jl. Penajam, Kampus UNMUL Gunung Kelua, Samarinda, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25026/jtpc.v8i2.634

Abstract

Secondary metabolites, a type of bioactive molecule with many functions, are abundant in Araucaria Heterophylla. The secondary metabolites flavonoids, phanolic acid, and tannin have been found to have anti-inflammatory, antiviral, antibacterial, antioxidant, and anticancer properties. The present study was conducted to analyze the phytochemical and determine the total flavonoid, tannin, phenolic content of Araucaria Heterophylla leaves extract using two different solvents (methanol and dichloromethane) using UV-Vis spectrophotometric. The plant was identified by NHB (ID No: DACB 48435) and prepared the methanolic extract to estimate the total content of tannin, phenolic & flavonoid in Araucaria Heterophylla. Folin-ciocaltu method was used for the investigation of total phenolic and tannin content. The A. heterophylla leaf methanolic and dichloromethane extract had remarkable antioxidant effects due to its high flavonoid and phenolic content. This standardised bioactive ingredient could be used in many phytopharmaceutical preparations
Co-Authors Afrin, Sadia Akter, Sadia Azmee, Marzan Azmee, Raiyan Ghosh, Ankita Ghosh, Susmita Hasan, Akayed Hasan, Ali Mohamod Wasaf Iqbal, Hrishik Jakir, Fatiha Nishan, Mufassir Ahmad Paul, Shimanta Sayeed, Md Abu Syrmos, Nikolaos Uddin, Mohammed Burhan