Skeleton scintigraphy with 99mTc-technefor was conducted in 71 patients with bone and joint tuberculosis and in 3 patients with nonspecific spinal diseases. The method was found to be highly sensitive in the diagnosis of a specific process, its localization, dissemination and activity. A correlation was revealed between the quantitative characteristics of isotope accumulation and morphologic signs of tuberculosis activity. Simultaneous visualization of the kidneys made it possible to diagnose their pathology.
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An overview of the use of cutting-edge artificial intelligence (AI) modeling to produce synthetic medical data (SMD) in decentralized clinical machine learning (ML) for ovarian cancer(OC) and ovarian lymphoma(OL).
J Ultrasound
January 2025
, Costa Contina street n. 19, 66054, Vasto, Chieti, Italy.
Aim: o point out how novel analysis tools of AI can make sense of the data acquired during OL and OC diagnosis and treatment in an effort to help improve and standardize the patient pathway for these disease.
Material And Methods: ultilizing programmed detection of heterogeneus OL and OC habitats through radiomics and correlate to imaging based tumor grading plus a literature review.
Results: new analysis pipelines have been generated for integrating imaging and patient demographic data and identify new multi-omic biomarkers of response prediction and tumour grading using cutting-edge artificial intelligence (AI) in OL and OC.
[Psychological aspects in occupational dermatology].
Dermatologie (Heidelb)
January 2025
Sektion Berufsdermatologie, Zentrum Hautklinik, Universitätsklinikum Heidelberg, Ruprecht-Karls-Universität Heidelberg, Voßstr. 2, 69115, Heidelberg, Deutschland.
The prevalence of psychological disorders in the general population and, therefore, in dermatological and allergological patients continues to increase. Psychodermatology as a branch of dermatology is also becoming ever more relevant in occupational dermatology. Psychological comorbidities and cofactors like depression and anxiety disorders or stress are increasingly important, which must be considered regarding diagnostics and therapy selection.
View Article and Find Full Text PDF[New methods at the transition from research to routine diagnostics].
Pathologie (Heidelb)
January 2025
Institut für Pathologie, Fachbereich Thorax- und Molekularpathologie, Universitätsmedizin Göttingen, Robert-Koch-Straße 40, 37075, Göttingen, Deutschland.
Background: Pathology, traditionally focused on classification and diagnosis, is continuously evolving through new technologies. Advances in proteomics, epigenetics, tissue staining, and 3D imaging expand the possibilities of classical morphology.
Aim Of The Study: The aim of this study was to investigate how modern technologies can improve diagnostic accuracy and therapy selection and how they can be integrated into pathologic routine diagnostics.
Estimates of the burden of skin melanoma in Italy: update to 2024.
Ital J Dermatol Venerol
January 2025
Emilia-Romagna Cancer Registry, Romagna Unit, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) Dino Amadori, Meldola, Forlì, Italy.
Background: The epidemiology of skin melanoma (SM) is rapidly changing. Therefore, we aimed at updating up to 2024 the Italian estimates on SM providing the number of incident and prevalent cases, the deaths and the distribution by stage at diagnosis.
Methods: Incidence was extrapolated from age- and sex-specific International Agency for Research on Cancer (IARC) estimates from 2022 to 2025.
Multi-study fMRI outlooks on subcortical BOLD responses in the stop-signal paradigm.
Elife
January 2025
Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, Netherlands.
This study investigates the functional network underlying response inhibition in the human brain, particularly the role of the basal ganglia in successful action cancellation. Functional magnetic resonance imaging (fMRI) approaches have frequently used the stop-signal task to examine this network. We merge five such datasets, using a novel aggregatory method allowing the unification of raw fMRI data across sites.
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