Background and Aims: Artificial Intelligence (AI) beginning to integrate in healthcare, is ushering in a transformative era, impacting diagnostics, altering personalized treatment, and significantly improving operational efficiency. The study aims to describe AI in healthcare, including important technologies like robotics, machine learning (ML), deep learning (DL), and natural language processing (NLP), and to investigate how these technologies are used in patient interaction, predictive analytics, and remote monitoring. The goal of this review is to present a thorough analysis of AI's effects on healthcare while providing stakeholders with a road map for navigating this changing environment. Methods: This review analyzes the impact of AI on healthcare using data from the Web of Science (2014–2024), focusing on keywords like AI, ML, and healthcare applications. It examines the uses and effects of AI on healthcare by synthesizing recent literature and real‐world case studies, such as Google Health and IBM Watson Health, highlighting AI technologies, their useful applications, and the difficulties in putting them into practice, including problems with data security and resource limitations. The review also discusses new developments in AI, and how they can affect society. Results: The findings demonstrate how AI is enhancing the skills of medical professionals, enhancing diagnosis, and opening the door to more individualized treatment plans, as reflected in the steady rise of AI‐related healthcare publications from 158 articles (3.54%) in 2014 to 731 articles (16.33%) by 2024. Core applications like remote monitoring and predictive analytics improve operational effectiveness and patient involvement. However, there are major obstacles to the mainstream implementation of AI in healthcare, including issues with data security and budget constraints. Conclusion: Healthcare may be transformed by AI, but its successful use requires ethical and responsible use. To meet the changing demands of the healthcare sector and guarantee the responsible application of AI technologies, the evaluation highlights the necessity of ongoing research, instruction, and multidisciplinary cooperation. In the future, integrating AI responsibly will be essential to optimizing its advantages and reducing related dangers.

Ficus carica Linn. (Moraceae) is commonly known as edible fig. The leaves, roots, fruits and latex of the plant are medicinally used in different diseases. The leaves are claimed to be effective in various inflammatory conditions like painful or swollen piles, insect sting and bites. However, there has been no report on anti-inflammatory and antioxidant activity of F. carica leaves. Therefore the aim of this study was to evaluate the anti-inflammatory and antioxidant activity of F. carica leaves. Our study validated the traditional claim with pharmacological data. Anti-inflammatory and antioxidant activity of the drug could be due to the presence of steroids and flavanoids, respectively, which are reported to be present in the drug. Furthermore, the anti-inflammatory activity of the drug could be due to its free radical scavenging activity. Further work is also required to isolate and characterise the active constituents responsible for the anti-inflammatory activities.

To assess the hepatoprotective effect of Solanum xanthocarpum (S. xanthocarpum) fruit extract against antitubercular drug-induced liver toxicity in experimental animals. Ethanolic (50%) fruit extract of S. xanthocarpum (100, 200 and 400 mg/kg bw) was administered daily for 35 days in experimental animals. Liver toxicity was induced by combination of three antitubercular drugs [isoniazid (I) 7.5 mg/kg, rifampicin (R) 10 mg/kg and pyrazinamide (P) 35 mg/kg] given orally as suspension for 35 days in rats. The hepatoprotective activity was assessed using various biochemical parameters like aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatise (ALP), total bilirubin (TBL), albumin (ALB), total protein (TP), lactate dehydroginase (LDH), and serum cholesterol (CHL). Meanwhile, in vivo antioxidant activities as lipid peroxidation (LPO), reduced glutathione (GSH), superoxide dismutase (SOD) and catalase (CAT) were measured in rat liver homogenate. The biochemical observations were supplemented by histopathological examination. The results demonstrated that treatment with S. xanthocarpum significantly (P<0.05-P<0.001) and dose-dependently prevented drug induced increase in serum levels of hepatic enzymes. Furthermore, S. xanthocarpum significantly (up to P<0.001) reduced the LPO in the liver tissue and restored activities of defence antioxidant enzymes GSH, SOD and CAT towards normal levels. Histopathology of the liver tissue showed that S. xanthocarpum attenuated the hepatocellular necrosis and led to reduction in inflammatory cells infiltration. The results of this study strongly indicate the protective effect of S. xanthocarpum against liver injury which may be attributed to its hepatoprotective activity, and thereby scientifically support its traditional use.

Ocular drug delivery presents significant challenges due to intricate anatomy and the various barriers (corneal, tear, conjunctival, blood-aqueous, blood-retinal, and degradative enzymes) within the eye. Lipid-based nanoparticles (LNPs) have emerged as promising carriers for ocular drug delivery due to their ability to enhance drug solubility, improve bioavailability, and provide sustained release. LNPs, particularly solid lipid nanoparticles (SLNs), nanostructured lipid carriers (NLCs), and cationic nanostructured lipid carriers (CNLCs), have emerged as promising solutions for enhancing ocular drug delivery. This review provides a comprehensive summary of lipid nanoparticle-based drug delivery systems, emphasizing their biocompatibility and efficiency in ocular applications. We evaluated research and review articles sourced from databases such as Google Scholar, TandFonline, SpringerLink, and ScienceDirect, focusing on studies published between 2013 and 2023. The review discusses the materials and methodologies employed in the preparation of SLNs, NLCs, and CNLCs, focusing on their application as proficient carriers for ocular drug delivery. CNLCs, in particular, demonstrate superior effectiveness attributed due to their electrostatic bioadhesion to ocular tissues, enhancing drug delivery. However, continued research efforts are essential to further optimize CNLC formulations and validate their clinical utility, ensuring advancements in ocular drug delivery technology for improved patient outcomes.