THE EFFECTIVENESS OF THE ROLE OF THE RADIOLOGY DEPARTMENT IN CONDUCTING AND INTERPRETING MEDICAL DIAGNOSTIC TESTS
Main Article Content
Keywords
Radiology nurses, Diagnostic tests, Imaging procedures, Patient care, Interpretation
Abstract
Radiologists are critical in healthcare, particularly in performing and deciphering therapeutic examinations. This basic audit investigates the different parts of radiologists within the symptomatic handle and highlights their significance in quiet care and results. Key zones examined incorporate modest planning, procedural back, picture translation, and their part in collaboration with other doctors. This article summarizes the existing writing and analyzes the effect of radiologists on demonstrative precision, persistent security, and general care. In expansion, recommendations were made to move forward the part of radiologists in expressive services.
References
2. Narang, A., Bae, R., Hong, H., Thomas, Y., Surette, S., Cadieu, C., ...& Thomas, J. D. (2021). Utility of a deep-learning algorithm to guide novices to acquire echocardiograms for limited diagnostic use. JAMA cardiology, 6(6), 624-
3. 632.https://jamanetwork.com/journals/jamacardiology/article-abstract/2776714
4. Kuo, R. Y., Harrison, C., Curran, T. A., Jones, B., Freethy, A., Cussons, D., ...& Furniss, D. (2022). Artificial intelligence in fracture detection: a systematic review and metaanalysis. Radiology, 304(1), 50-62.https://pubs.rsna.org/doi/abs/10.1148/radiol.211785
5. Mossa-Basha, M., Meltzer, C. C., Kim, D. C., Tuite, M. J., Kolli, K. P., & Tan, B. S. (2020). Radiology department preparedness for COVID-19: radiology scientific expert review panel. Radiology, 296(2), E106-E112.https://pubs.rsna.org/doi/abs/10.1148/radiol.2020200988
6. Braais, M., Hoskin, P., Andritsch, E., Banks, I., Beishon, M., Boyle, H., ...& Poortmans, P. (2020). ECCO essential requirements for quality cancer care: prostate cancer. Critical Reviews in Oncology/Hematology, 148, 102861.https://www.sciencedirect.com/science/article/pii/S1 040842819302471
7. Mollura, D. J., Culp, M. P., Pollack, E., Battino, G., Scheel, J. R., Mango, V. L., ...& Dako, F. (2020). Artificial intelligence in low-and middle-income countries: innovating global health radiology. Radiology, 297(3), 513-520.https://pubs.rsna.org/doi/abs/10.1148/radiol.2020201434
8. Wynants, L., Van Calster, B., Collins, G. S., Riley, R. D., Heinze, G., Schuit, E., ...& van Smeden, M. (2020). Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal. bmj, 369.https://www.bmj.com/content/369/bmj.m1328.long
9. Kapoor, N., Lacson, R., & Khorasani, R. (2020). Workflow applications of artificial intelligence in radiology and an overview of available tools. Journal of the American College of Radiology, 17(11), 1363-1370.https://www.sciencedirect.com/science/article/pii/S1546144020308760
10. Austin, E. E., Blakely, B., Tufanaru, C., Selwood, A., Braithwaite, J., & Clay-Williams, R. (2020). Strategies to measure and improve emergency department performance: a scoping review. Scandinavian journal of trauma, resuscitation and emergency medicine, 28(1), 1-14.https://sjtrem.biomedcentral.com/articles/10.1186/s13049-02000749-2
11. Abbasgholizadeh Rahimi, S., Légaré, F., Sharma, G., Archambault, P., Zomahoun, H. T. V., Chandavong, S., ...& Légaré, J. (2021). Application of artificial intelligence in community-based primary health care: systematic scoping review and critical appraisal. Journal of Medical Internet Research, 23(9), e29839.https://www.jmir.org/2021/9/e29839/
12. Adliene, D., Griciene, B., Skovorodko, K., Laurikaitiene, J., & Puiso, J. (2020). Occupational radiation exposure of health professionals and cancer risk assessment for Lithuanian nuclear medicine workers. Environmental research, 183, 109144.https://www.sciencedirect.com/science /article/pii/S0013935120300360
13. Wu, J. T., Wong, K. C., Gur, Y., Ansari, N., Karargyris, A., Sharma, A., ...& Syeda-Mahmood, T. (2020). Comparison of chest radiograph interpretations by artificial intelligence algorithm vs radiology residents. JAMA network open, 3(10), e2022779e2022779.https://www.mdpi.com /2076-3417/10/22/8298
14. Schaffter, T., Buist, D. S., Lee, C. I., Nikulin, Y., Ribli, D., Guan, Y., ...& DM DREAM Consortium. (2020). Evaluation of combined artificial intelligence and radiologist assessment to interpret screening mammograms. JAMA network open, 3(3), e200265e200265. https://jamanetwork.com/journals/jamanetworkopen/article-abstract/2761795
15. Barazzoni, R., Jensen, G. L., Correia, M. I. T., Gonzalez, M. C., Higashiguchi, T., Shi, H. P., ...& Compher, C. (2022). Guidance for assessment of the muscle mass phenotypic criterion for the Global Leadership Initiative on Malnutrition (GLIM) diagnosis of malnutrition. Clinical Nutrition, 41(6), 1425-1433.https://www.sciencedirect.com/science/article/pii/S026156142 2000449
16. Nichols, J. H., Alter, D., Chen, Y., Isbell, T. S., Jacobs, E., Moore, N., & Shajani-Yi, Z. (2020). AACC guidance document on management of point-of-care testing. The Journal of Applied Laboratory Medicine, 5(4), 762-787.https://academic.oup.com/jalm/articlepdf/doi/10.1093/ jalm/jfaa059/33448951/jfaa059.pdf
17. Van’t Sant, I., Engbersen, M. P., Bhairosing, P. A., Lambregts, D. M. J., Beets-Tan, R. G. H., van Driel, W. J., ... & Lahaye, M. J. (2020). Diagnostic performance of imaging for the detection of peritoneal metastases: a meta-analysis. European radiology, 30, 3101-3112. https://www.neurology.org/doi/abs/10.1212/WNL.0000000000207740
18. Ashcraft, S., Wilson, S. E., Nyström, K. V., Dusenbury, W., Wira, C. R., Burrus, T. M., & American Heart Association Council on Cardiovascular and Stroke Nursing and the Stroke Council. (2021). Care of the patient with acute ischemic stroke (prehospital and acute phase of care): update to the 2009 comprehensive nursing care scientific statement: a scientific statement from the American Heart Association. Stroke, 52(5), e164e178. https://www.sciencedirect.com/ /article/pii/S0261561419331516
19. Morgan, D. J., Pineles, L., Owczarzak, J., Magder, L., Scherer, L., Brown, J. P., ...& Korenstein, D. (2021). Accuracy of practitioner estimates of probability of diagnosis before and after testing. JAMA internal medicine, 181(6), 747-755.https://jamanetwork.com/journals/jamainternal medicine/article-abstract/2778364
20. Cook, D. A., Oh, S. Y., & Pusic, M. V. (2020). Accuracy of physicians’ electrocardiogram interpretations: a systematic review and meta-analysis. JAMA internal medicine, 180(11), 1461-1471.https://jamanetwork.com/journals/jamainternalmedicine/articleabstract/2771093