Search

Oral cancer (OC) is one of the most common forms of head and neck cancer and continues to have the lowest survival rates worldwide, even with advancements in research and therapy. The prognosis of OC has not significantly improved in recent years, presenting a persistent challenge in the biomedical field. In the field of oncology, artificial intelligence (AI) has seen rapid development, with notable successes being reported in recent times. This systematic review aimed to critically appraise the available evidence regarding the utilization of AI in the diagnosis, classification, and prediction of oral cancer (OC) using histopathological images. An electronic search of several databases, including PubMed, Scopus, Embase, the Cochrane Library, Web of Science, Google Scholar, and the Saudi Digital Library, was conducted for articles published between January 2000 and January 2023. Nineteen articles that met the inclusion criteria were then subjected to critical analysis utilizing QUADAS-2, and the certainty of the evidence was assessed using the GRADE approach. AI models have been widely applied in diagnosing oral cancer, differentiating normal and malignant regions, predicting the survival of OC patients, and grading OC. The AI models used in these studies displayed an accuracy in a range from 89.47% to 100%, sensitivity from 97.76% to 99.26%, and specificity ranging from 92% to 99.42%. The models' abilities to diagnose, classify, and predict the occurrence of OC outperform existing clinical approaches. This demonstrates the potential for AI to deliver a superior level of precision and accuracy, helping pathologists significantly improve their diagnostic outcomes and reduce the probability of errors. Considering these advantages, regulatory bodies and policymakers should expedite the process of approval and marketing of these products for application in clinical scenarios. [ABSTRACT FROM AUTHOR]

Purpose To examine the various facets of job satisfaction among radiographers in Saudi Arabia and compare the influential contributing factors locally and internationally. Methods A cross-sectional survey was conducted in June and July 2020 with an electronic questionnaire distributed to radiographers in Saudi Arabia. The validated Job Satisfaction Survey was used to measure overall job satisfaction and specific satisfaction regarding pay, promotions, supervision, benefits, contingent rewards, operating conditions, coworkers, nature of work, and communication (total Job Satisfaction Survey score can range from 36 to 216). Additional personal and work-related characteristics were collected as explanatory variables. Data were analyzed with descriptive and inferential statistics, including 1-way analysis of variance, independent sample t test, and Spearman correlation. Results A total of 412 radiographers in Saudi Arabia completed the survey. The total job satisfaction score was 140.0 (95% confidence interval [CI], 138.7-141.2), showing that 6 respondents (1.5%) were dissatisfied with their job, while the remaining majority were neutral (63%) or satisfied (36%). The radiographers were satisfied with the nature of work, contingent rewards, and coworkers. However, they were less satisfied with promotions, pay, operating conditions, and benefits. The only significant variable in overall job satisfaction was the working sector (P = .03), with radiographers working at Ministry of Health hospitals who were more satisfied than were their colleagues who worked at other types of facilities. Discussion The radiographers in Saudi Arabia had higher overall job satisfaction than had other allied health science professionals in Saudi Arabia. The differences in job satisfaction subscales between radiographers from different countries suggest that their job satisfaction likely is related to culture and socioeconomics. Job satisfaction improvement programs should be tailored for each radiographer's community. Conclusion Radiographers in Saudi Arabia expressed moderate to high job satisfaction, which is relatively higher than their international peers and national colleagues in physical therapy and nursing. These job satisfaction results call for governmental policymakers to focus their efforts on improving radiographer promotion schemes and career development. [ABSTRACT FROM AUTHOR]