Publications by authors named "K A Hietala"
Article Synopsis
- * Manually labeling unstructured medical reports for DR analysis is labor-intensive, leading to the development of DR-GPT, a large language model designed to classify DR severity from these reports.
- * DR-GPT demonstrated high accuracy in severity classification and improved the performance of image classifiers when its annotations were combined with fundus images, showcasing the potential of AI in healthcare.
Background: As the retina is suggested to mirror the brain, we hypothesized that diabetic retinopathy and macular edema are indicative of stroke risk in type 1 diabetes and sought to assess this association in individuals with type 1 diabetes.
Methods: We included 1,268 adult FinnDiane Study participants with type 1 diabetes (age 38.7 ± 11.
A formally certified end-to-end implementation of Shor's factorization algorithm.
Proc Natl Acad Sci U S A
May 2023
Quantum computing technology may soon deliver revolutionary improvements in algorithmic performance, but it is useful only if computed answers are correct. While hardware-level decoherence errors have garnered significant attention, a less recognized obstacle to correctness is that of human programming errors-"bugs." Techniques familiar to most programmers from the classical domain for avoiding, discovering, and diagnosing bugs do not easily transfer, at scale, to the quantum domain because of its unique characteristics.
View Article and Find Full Text PDFBackground/aims: Diabetic retinopathy (DR) is associated and shares many risk factors with other diabetic complications, including inflammation. Bacterial infections, potent inducers of inflammation have been associated with the development of diabetic complications apart from DR. Our aim was to investigate the association between bacterial infections and DR.
View Article and Find Full Text PDFAims: The aim of this study was to investigate whether leisure-time physical activity (LTPA) is associated with the development of severe diabetic retinopathy in individuals with type 1 diabetes.
Methods: Prospective observational analysis as part of the Finnish diabetic nephropathy (FinnDiane) Study with a mean follow-up time of 10.7 years was performed.