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http://dx.doi.org/10.1186/s12889-023-16802-5 | DOI Listing |
EClinicalMedicine
December 2024
Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Background: Infant alertness and neurologic changes can reflect life-threatening pathology but are assessed by physical exam, which can be intermittent and subjective. Reliable, continuous methods are needed. We hypothesized that our computer vision method to track movement, pose artificial intelligence (AI), could predict neurologic changes in the neonatal intensive care unit (NICU).
View Article and Find Full Text PDFJ Med Case Rep
January 2025
Department of Surgery, University Hospital "Tsaritsa Joanna - ISUL", Medical University, Str. "Byalo More" No 8, Sofia, Bulgaria.
Background: McKittrick-Wheelock syndrome is an uncommon and severe disorder caused by large hypersecretory tumors located in the distal colorectal area. Excessive secretion from adenomas is an unusual clinical manifestation that leads to severe electrolyte and fluid depletion, subsequently resulting in kidney injury. Successful treatment relies on quick and cooperative decision-making for timely intervention.
View Article and Find Full Text PDFRev Med Chil
May 2024
Departamento de Nefrología, Clínica Dávila, Santiago, Chile.
Unlabelled: Uremic leontiasis ossia (ULO) is a rare manifestation of renal osteodystrophy in) patients with end-stage chronic kidney disease (CKD) and secondary hyperparathyroidism (SHPTH). It occurs due to increased osteoclastic activity secondary to high plasmatic parathyroid hormone (PTH) levels. This leads to bone deformation with thickening and massive enlargement of the cranial vault, resulting in a leonine face appearance.
View Article and Find Full Text PDFiScience
December 2024
Florida Institute of Technology, Department of Psychology, 150 W. University Dr., Melbourne, FL 32905, USA.
Episodic memory is accounted for with two processes: "familiarity" when generally recognizing an item and "recollection" when retrieving the full contextual details bound with the item. We tested a combination of item recognition confidence and source memory, focusing upon three conditions: "item-only hits with source unknown" ('item familiarity'), "low-confidence hits with correct source memory" ('context familiarity'), and "high-confidence hits with correct source memory" ('recollection'). Behaviorally, context familiarity was slower than the others during item recognition, but faster during source memory.
View Article and Find Full Text PDFSci Rep
January 2025
College of Computer and Data Science, Minjiang University, Fuzhou, 350018, China.
This study presents a novel approach to identifying meters and their pointers in modern industrial scenarios using deep learning. We developed a neural network model that can detect gauges and one or more of their pointers on low-quality images. We use an encoder network, jump connections, and a modified Convolutional Block Attention Module (CBAM) to detect gauge panels and pointer keypoints in images.
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