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Comment on "Dolphin and porpoise detections by the F-POD are not independent: Implications for sympatric species monitoring" [JASA Express Lett. 4, 031202 (2024)].
JASA Express Lett
January 2025
Schmalhausen Institute of Zoology of National Academy of Sciences of Ukraine, Bohdana Khmel'nyts'koho Street, 15, Kyiv 02000, Ukraine.
Dolphin and porpoise detections by the F-POD are not independent: Implications for sympatric species monitoring, Cosentino, Marcolin, Griffiths, Sánchez-Camí, and Tougaard [(2024). JASA Express Lett. 4, 031202] address a significant issue, the reliability of the discrimination of dolphins and porpoises in recordings of their acoustic clicks by F-POD loggers, but unfortunately present a misleading interpretation of the process and results.
View Article and Find Full Text PDFReview article: Efficacy of cyproheptadine in the management of serotonin toxicity following deliberate self-poisoning - A systematic review.
Emerg Med Australas
February 2025
Addiction Psychiatry and Toxicology, Northern Health, Melbourne, Victoria, Australia.
Serotonin toxicity is a potentially fatal condition caused by increased serotonergic activity in the central nervous system. Cyproheptadine, a serotonergic antagonist, is recommended for treatment; however, there is a lack of evidence to support its use. The present study aimed to evaluate the evidence for the use of cyproheptadine in the management of serotonin toxicity following deliberate self-poisoning.
View Article and Find Full Text PDFPredatory journals: what can we do to protect their prey?
Lancet
January 2025
La Tunisie Médicale, Tunis, Tunisia.
Development of a framework to structure decision-making in environmental and occupational health: A systematic review and Delphi study.
Environ Int
December 2024
Cochrane Canada and McMaster GRADE Centres & Department of Health Research Methods, Evidence and Impact, McMaster University, Health Sciences Centre, Room 2C14, 1280 Main Street West, Hamilton, ON L8S 4K1, Canada; School of Medicine, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44106, USA. Electronic address:
Background: Environmental and occupational health (EOH) assessments increasingly utilize systematic review methods and structured frameworks for evaluating evidence about the human health effects of exposures. However, there is no prevailing approach for how to integrate this evidence into decisions or recommendations. Grading of Recommendations Assessment, Development and Evaluation (GRADE) evidence-to-decision (EtD) frameworks provide a structure to support standardized and transparent consideration of relevant criteria to inform health decisions.
View Article and Find Full Text PDFLeveraging Natural Language Processing and Machine Learning Methods for Adverse Drug Event Detection in Electronic Health/Medical Records: A Scoping Review.
Drug Saf
January 2025
Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Background: Natural language processing (NLP) and machine learning (ML) techniques may help harness unstructured free-text electronic health record (EHR) data to detect adverse drug events (ADEs) and thus improve pharmacovigilance. However, evidence of their real-world effectiveness remains unclear.
Objective: To summarise the evidence on the effectiveness of NLP/ML in detecting ADEs from unstructured EHR data and ultimately improve pharmacovigilance in comparison to other data sources.
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