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Fulltext Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry-A Systematic Review

Ahmed N, Abbasi MS, Zuberi F, Qamar W, Halim MSB, Maqsood A, et al.

Biomed Res Int, 2021;2021:9751564.
PMID: 34258283 DOI: 10.1155/2021/9751564

OBJECTIVE: The objective of this systematic review was to investigate the quality and outcome of studies into artificial intelligence techniques, analysis, and effect in dentistry.
MATERIALS AND METHODS: Using the MeSH keywords: artificial intelligence (AI), dentistry, AI in dentistry, neural networks and dentistry, machine learning, AI dental imaging, and AI treatment recommendations and dentistry. Two investigators performed an electronic search in 5 databases: PubMed/MEDLINE (National Library of Medicine), Scopus (Elsevier), ScienceDirect databases (Elsevier), Web of Science (Clarivate Analytics), and the Cochrane Collaboration (Wiley). The English language articles reporting on AI in different dental specialties were screened for eligibility. Thirty-two full-text articles were selected and systematically analyzed according to a predefined inclusion criterion. These articles were analyzed as per a specific research question, and the relevant data based on article general characteristics, study and control groups, assessment methods, outcomes, and quality assessment were extracted.
RESULTS: The initial search identified 175 articles related to AI in dentistry based on the title and abstracts. The full text of 38 articles was assessed for eligibility to exclude studies not fulfilling the inclusion criteria. Six articles not related to AI in dentistry were excluded. Thirty-two articles were included in the systematic review. It was revealed that AI provides accurate patient management, dental diagnosis, prediction, and decision making. Artificial intelligence appeared as a reliable modality to enhance future implications in the various fields of dentistry, i.e., diagnostic dentistry, patient management, head and neck cancer, restorative dentistry, prosthetic dental sciences, orthodontics, radiology, and periodontics.
CONCLUSION: The included studies describe that AI is a reliable tool to make dental care smooth, better, time-saving, and economical for practitioners. AI benefits them in fulfilling patient demand and expectations. The dentists can use AI to ensure quality treatment, better oral health care outcome, and achieve precision. AI can help to predict failures in clinical scenarios and depict reliable solutions. However, AI is increasing the scope of state-of-the-art models in dentistry but is still under development. Further studies are required to assess the clinical performance of AI techniques in dentistry.
Preclinical Evidence for the Pharmacological Actions of Glycyrrhizic Acid: A Comprehensive Review

Rehman MU, Farooq A, Ali R, Bashir S, Bashir N, Majeed S, et al.

Curr Drug Metab, 2020;21(6):436-465.
PMID: 32562521 DOI: 10.2174/1389200221666200620204914

Glycyrrhiza glabra L. (Family: Fabaceae) is one of the important traditional medicinal plant used extensively in folk medicine. It is known for its ethnopharmacological value in curing a wide variety of ailments. Glycyrrhizin, an active compound of G. glabra, possesses anti-inflammatory activity due to which it is mostly used in traditional herbal medicine for the treatment and management of chronic diseases. The present review is focused extensively on the pharmacology, pharmacokinetics, toxicology, and potential effects of Glycyrrhizic Acid (GA). A thorough literature survey was conducted to identify various studies that reported on the GA on PubMed, Science Direct and Google Scholar.
Fulltext Long short term memory networks for predicting resilient Modulus of stabilized base material subject to wet-dry cycles

Al-Zubi MA, Ahmad M, Abdullah S, Khan BJ, Qamar W, Abdullah GMS, et al.

Sci Rep, 2024 Nov 13;14(1):27928.
PMID: 39537833 DOI: 10.1038/s41598-024-79588-5

The resilient modulus (MR) of different pavement materials is one of the most important input parameters for the mechanistic-empirical pavement design approach. The dynamic triaxial test is the most often used method for evaluating the MR, although it is expensive, time-consuming, and requires specialized lab facilities. The purpose of this study is to establish a new model based on Long Short-Term Memory (LSTM) networks for predicting the MR of stabilized base materials with various additives during wet-dry cycles (WDC). A laboratory dataset of 704 records has been used using input parameters, including WDC, ratio of calcium oxide to silica, alumina, and ferric oxide compound, Maximum dry density to the optimal moisture content ratio (DMR), deviator stress (σd), and confining stress (σ3). The results demonstrate that the LSTM technique is very accurate, with coefficients of determination of 0.995 and 0.980 for the training and testing datasets, respectively. The LSTM model outperforms other developed models, such as support vector regression and least squares approaches, in the literature. A sensitivity analysis study has determined that the DMR parameter is the most significant factor, while the σd parameter is the least significant factor in predicting the MR of the stabilized base material under WDC. Furthermore, the SHapley Additive exPlanations approach is employed to elucidate the optimal model and examine the impact of its features on the final result.
Hydatigera taeniaeformis in urban rats (Rattus rattus) in Faisalabad, Pakistan

Alvi MA, Li L, Ohiolei JA, Qamar W, Saqib M, Tayyab MH, et al.

Infect Genet Evol, 2021 Aug;92:104873.
PMID: 33905888 DOI: 10.1016/j.meegid.2021.104873

Hydatigera taeniaeformis formerly referred to as Taenia taeniaeformis is a cestode of cats (definitive hosts) and rodents (intermediate hosts). The prevalence of the metacestode larval stage has been reported in rodents in many parts of the world even though the genetic polymorphisms or intraspecies variation is still understudied. Here, we report a prevalence of 22.09% (38/172) from an urban rodent population in Pakistan and a nucleotide diversity (cox1) of 0.00463 among the population. Infection was higher in male (27.85%) and adult (32.29%) rats than female and sub-adult/young rats. Interestingly, The median-joining network and phylogenetic construction comprising isolates from China, Japan, Kenya, Laos, Malaysia, Senegal, the United Arab Emirates, and countries in Europe demonstrated that Pakistani H. taeniaeformis are closer to Asian and African population than those of European origin. The results of the study will add-in preliminary data for H. taeniaeformis and will also contribute to understand the global molecular epidemiology and population structure of H. taeniaeformis.