METHODS: In order to solve this problem, this paper proposes an end-to-end framework based on BERT for NER and RE tasks in electronic medical records. Our framework first integrates NER and RE tasks into a unified model, adopting an end-to-end processing manner, which removes the limitation and error propagation of multiple independent steps in traditional methods. Second, by pre-training and fine-tuning the BERT model on large-scale electronic medical record data, we enable the model to obtain rich semantic representation capabilities that adapt to the needs of medical fields and tasks. Finally, through multi-task learning, we enable the model to make full use of the correlation and complementarity between NER and RE tasks, and improve the generalization ability and effect of the model on different data sets.
RESULTS AND DISCUSSION: We conduct experimental evaluation on four electronic medical record datasets, and the model significantly out performs other methods on different datasets in the NER task. In the RE task, the EMLB model also achieved advantages on different data sets, especially in the multi-task learning mode, its performance has been significantly improved, and the ETE and MTL modules performed well in terms of comprehensive precision and recall. Our research provides an innovative solution for medical image and signal data.
METHODS: The PRISMA guidelines were adopted for this systematic literature review. Prominent academic databases such as Web of Science, PubMed, ProQuest, Cochrane Library, China National Knowledge Infrastructure (CNKI) and PsycINFO were searched to find eligible studies published before Aug 2021. The overall quality of the articles was checked using the "QualSyst" tool by Kmet et al.
RESULTS: From among 600 papers, 23 met the inclusion criteria and were incorporated into our systematic review. All of the studies were randomized controlled trials. The following thematic areas emerged as a result of the content analysis: study selection and design, as well as study characteristics (participants, intervention, comparisons, and outcomes).
DISCUSSION AND CONCLUSION: The literature on exercise and psychological interventions for smartphone addiction is scarce. There is a need to introduce new interventions and to validate the effectiveness of combined interventions. Our findings suggest that exercise and psychological interventions may help to reduce smartphone addiction. This combination was more effective compare to exercise or psychological intervention on mental health and addiction among university students. Future research should combine exercise and psychological interventions, focusing on university students, especially females, who are vulnerable to smartphone addiction. Further studies should focus on the cross-section of neuropsychology, cognitive psychology, and sports science to provide combined interventions in physiological and psychological direction.
SYSTEMATIC REVIEW REGISTRATION: https://www.crd.york.ac.uk/prospero, identifier: CRD42021278037.
RESULTS: Here, we present draft genome information for five agriculturally, biologically, medicinally, and economically important underutilized plants native to Africa: Vigna subterranea, Lablab purpureus, Faidherbia albida, Sclerocarya birrea, and Moringa oleifera. Assembled genomes range in size from 217 to 654 Mb. In V. subterranea, L. purpureus, F. albida, S. birrea, and M. oleifera, we have predicted 31,707, 20,946, 28,979, 18,937, and 18,451 protein-coding genes, respectively. By further analyzing the expansion and contraction of selected gene families, we have characterized root nodule symbiosis genes, transcription factors, and starch biosynthesis-related genes in these genomes.
CONCLUSIONS: These genome data will be useful to identify and characterize agronomically important genes and understand their modes of action, enabling genomics-based, evolutionary studies, and breeding strategies to design faster, more focused, and predictable crop improvement programs.
METHODS: A comprehensive systematic search was carried out in PubMed/MEDLINE, SCOPUS, Web of Science, and EMBASE databases for (nested) case-control studies that reported the levels of IGF-1 and IGFBP in GC cases and healthy controls, from inception until October 2020. Weighted mean difference (WMD) was calculated for estimating combined effect size. Subgroup analysis was performed to identify the source of heterogeneity among studies.
RESULTS: We found eight and five eligible studies (with 1541 participants) which provided data for IGF-1 and IGFBP, respectively. All studies on IGFBP reported the IGFBP-3 isoform. The pooled results indicate that GC patients had significantly lower serum IGF-1 [WMD = -26.21 ng/mL (95% CI, -45.58 to -6.85; P = .008)] and IGFBP-3 [WMD = -0.41 ng/mL (95% CI, -0.80 to -0.01; P = .04; I2 = 89.9%; P