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http://dx.doi.org/10.1038/s41372-024-01990-8 | DOI Listing |
Nat Methods
January 2025
OncoRNALab, Cancer Research Institute Ghent (CRIG), Department of Biomolecular Medicine, Ghent University, Ghent, Belgium.
Dermatol Ther (Heidelb)
January 2025
Institute and Comprehensive Center Inflammation Medicine, University of Lübeck, Lübeck, Germany.
NPJ Digit Med
January 2025
Centre for Epidemiology Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, United Kingdom.
Machine learning has increasingly been applied to predict opioid-related harms due to its ability to handle complex interactions and generating actionable predictions. This review evaluated the types and quality of ML methods in opioid safety research, identifying 44 studies using supervised ML through searches of Ovid MEDLINE, PubMed and SCOPUS databases. Commonly predicted outcomes included postoperative opioid use (n = 15, 34%) opioid overdose (n = 8, 18%), opioid use disorder (n = 8, 18%) and persistent opioid use (n = 5, 11%) with varying definitions.
View Article and Find Full Text PDFJ Craniofac Surg
January 2025
Scar and Wound Treatment Center, Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, P. R. China.
Background: Compared with direct linear resection, the triangular flap insertion method is a correction method that purportedly reduces the incision tension of dog ears deformity. Randomized clinical trials comparing these 2 methods seem to be limited or absent.
Objective: A randomized study was planned to compare the cosmetic effect and scar in the defect area between the triangular flap insertion method and direct linear resection in the repair of dog ear deformities after the suture of the facial circular defect.
In the vibrant linguistic landscape of Bengali, spoken by millions in Bangladesh and India, the gap between saintly and common terms is culturally and computationally significant. Recognising this, we introduce BanglaBlend, a pioneering dataset created to capture these stylistic distinctions. BanglaBlend comes with 7350 annotated sentences, 3675 in saintly form and 3675 in common form, covering a crucial need in natural language processing (NLP) resources for Bangla.
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