At present no adequate annotation guidelines exists for incident report learning. This study aims at utilizing multiple quantitative and qualitative evidence to validate annotation guidelines for incident reporting of medication errors. Through multiple approaches via annotator training, annotation performance evaluation, exit surveys, and user and expert interviews, a mixed methods explanatory sequential design was utilized to collect 2-stage evidence for validation. We recruited two patient safety experts to participate in piloting, three annotators to receive annotation training and provide user feedback, and two incident report system designers to offer expert comments. Regarding the annotation performance evaluation, the overall accuracy reached 97% and 90% for named entity identification and attribute identification respectively. Participants provided invaluable comments and opinions towards improving the annotation methods. The mixed methods approach created a significant evidential basis for the use of annotation guidelines for incident report of medication errors. Further expansion of the guidelines and external validity present options for future research.
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http://dx.doi.org/10.3233/SHTI220095 | DOI Listing |
J Pharm Biomed Anal
January 2025
Institute of Pharmaceutical Sciences, Pharmaceutical (Bio-)Analysis, University of Tübingen, Auf der Morgenstelle 8, Tübingen 72076, Germany. Electronic address:
Alkaptonuria (AKU) is a rare autosomal-recessive disease which is characterized through black urine and ochronosis. It is caused by deficiency of the enzyme Homogentisate 1,2-dioxygenase in the Phenylalanine/Tyrosine degradation pathway which leads to the accumulation of Homogentisic acid (HGA). Urine was provided by AKU patients and healthy controls.
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Anhui BioX-Vision Biological Technology Co., Ltd, Hefei, 230031, Anhui, China.
The identification and categorization of circulating tumor cells (CTCs) in peripheral blood are imperative for advancing cancer diagnostics and prognostics. The intricacy of various CTCs subtypes, coupled with the difficulty in developing exhaustive datasets, has impeded progress in this specialized domain. To date, no methods have been dedicated exclusively to overcoming the classification challenges of CTCs.
View Article and Find Full Text PDFBMC Plant Biol
January 2025
CAS Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, Hubei, 430074, China.
Background: Red raspberry (Rubus idaeus L.) is a renowned fruit plant with significant medicinal value. Its nuclear genome and chloroplast genome (plastome) have been reported, while there is a lack of genetic information on its mitogenome.
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January 2025
Children's Medical Center, Peking University First Hospital, No.5 Le Yuan Road, Daxing District, 100034, Beijing, China.
Long-read sequencing has emerged as a transformative technology in recent years, offering significant potential for the molecular diagnosis of unresolved genetic disorders. Despite its promise, the comprehensive detection and clinical annotation of genomic variants remain intricate and technically demanding. We present SUMMER, an integrated and structured workflow specifically designed to process raw Nanopore sequencing reads.
View Article and Find Full Text PDFData Brief
February 2025
Arabic Department, University of Sharjah, UAE.
This paper introduces the Morphologically-Analyzed and Syntactically-Annotated Quran (MASAQ) dataset, a comprehensive resource designed to address the scarcity of annotated Quranic Arabic corpora and facilitate the development of advanced Natural Language Processing (NLP) models. The Quran, being a cornerstone of classical Arabic, presents unique challenges for NLP due to its sacred nature and complex linguistic features. MASAQ provides a detailed syntactic and morphological annotation of the entire Quranic text, utilizing a rigorously verified text from Tanzil.
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