Search

Your search keyword '"Mandal, Shobha"' showing total 22 results
Start Over Author "Mandal, Shobha" Journal cureus
22 results on '"Mandal, Shobha"'

21. Co-infectious Uveitis With Syphilis and Lyme Disease: A Case Report.

Author

Mandal S, Tayyab H, Mandal SC, and Sideeg A

Abstract

Uveitis is the inflammation of the uveal tract (i.e., iris, ciliary body, and choroid). Uveitis is categorized into the following three types based on the anatomical location of inflammation: anterior, intermediate, and posterior uveitis. Severe cases may lead to panuveitis, where all three layers may become inflamed potentially resulting in permanent vision loss. Uveitis can arise from different underlying disorders, including infectious causes or autoimmune disorders. Syphilis and Lyme disease are uncommon causes of uveitis. Eye involvement can occur at any stage in Lyme disease, characterized by diverse manifestations such as conjunctivitis, episcleritis, keratitis, uveitis, neuroretinitis, and retinal vasculitis. Patients may present with symptoms of blurred vision, eye pain or discomfort, visual floaters, headache, or intolerance to light. Patients can risk vision loss if not diagnosed and treated promptly., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2024, Mandal et al.)

Published
2024
Full Text
View/download PDF

22. Revolutionizing Breast Cancer Detection With Artificial Intelligence (AI) in Radiology and Radiation Oncology: A Systematic Review.

Author

Rentiya ZS, Mandal S, Inban P, Vempalli H, Dabbara R, Ali S, Kaur K, Adegbite A, Intsiful TA, Jayan M, Odoma VA, and Khan A

Abstract

The number one cause of cancer in women worldwide is breast cancer. Over the last three decades, the use of traditional screen-film mammography has increased, but in recent years, digital mammography and 3D tomosynthesis have become standard procedures for breast cancer screening. With the advancement of technology, the interpretation of images using automated algorithms has become a subject of interest. Initially, computer-aided detection (CAD) was introduced; however, it did not show any long-term benefit in clinical practice. With recent advances in artificial intelligence (AI) methods, these technologies are showing promising potential for more accurate and efficient automated breast cancer detection and treatment. While AI promises widespread integration in breast cancer detection and treatment, challenges such as data quality, regulatory, ethical implications, and algorithm validation are crucial. Addressing these is essential for fully realizing AI's potential in enhancing early diagnosis and improving patient outcomes in breast cancer management. In this review article, we aim to provide an overview of the latest developments and applications of AI in breast cancer screening and treatment. While the existing literature primarily consists of retrospective studies, ongoing and future prospective research is poised to offer deeper insights. Artificial intelligence is on the verge of widespread integration into breast cancer detection and treatment, holding the potential to enhance early diagnosis and improve patient outcomes., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2024, Rentiya et al.)

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results