How to be a named or designated doctor for looked-after children

There are approximately 100,000 looked after children within the care system in the UK. Children and young people enter the care system with unmet health needs and missed routine health screening and poor management of existing health conditions. They may have delayed development due to neglect and many have unmet and significant emotional health needs. Named and Designated Doctors for looked after children are passionate experts willing to stand up and advocate for children and young people. They exert influence on a larger scale within the healthcare system, offering senior level problem solving and contributions to interagency liaison and service planning. The Named and Designated roles are statutory in the UK. However, each of the four nations in the UK has slightly different versions of looked after children and safeguarding children legislation. The RCPCH, RCN and RCGPs, which support all four UK nations, have also produced guidance - Looked After Children: Roles and Competencies of Healthcare Staff. The document sets out the required knowledge, skills, and competencies at each level of health professional working with children and young people. This short review summarises some of the key aspects of the role fulfilled by Named and Designated doctors and offers practical advice to those considering the role and some real world examples of how it can be successfully implemented.     

Enhancing HMM-based biomedical named entity recognition by studying special phenomena

The purpose of this research is to enhance an HMM-based named entity recognizer in the biomedical domain. First, we analyze the characteristics of biomedical named entities. Then, we propose a rich set of features, including orthographic, morphological, part-of-speech, and semantic trigger features. All these features are integrated via a Hidden Markov Model with back-off modeling. Furthermore, we propose a method for biomedical abbreviation recognition and two methods for cascaded named entity recognition. Evaluation on the GENIA V3.02 and V1.1 shows that our system achieves 66.5 and 62.5 F-measure, respectively, and outperforms the previous best published system by 8.1 F-measure on the same experimental setting. The major contribution of this paper lies in its rich feature set specially designed for biomedical domain and the effective methods for abbreviation and cascaded named entity recognition. To our best knowledge, our system is the first one that copes with the cascaded phenomena.     

狼疮性肾炎的中医病名及分型辨治研究综述

狼疮性肾炎是系统性红斑狼疮最主要的内脏损害,是临床最主要的继发性肾脏疾病之一。中医药对本病的治疗具有一定特色,形成了一定的中医理论。本文主要从中医学中有关狼疮性肾炎的病名、近年来对其病因病机、辨证分型论治方面的研究进行综述。     

针药配伍对高血压大鼠血清ACE、血浆AngⅡ含量的影响

目的：观察清肝益气降压方配伍针刺太冲、太溪、足三里对高血压大鼠血清ACE、血浆AngⅡ含量的影响,探讨针药配伍的科学性和可行性。方法：采用正交设计安排实验,将造模成功大鼠分别给予清肝益气降压方和针刺,连续治疗2周后,测定大鼠血压、血清ACE、血浆AngⅡ含量。结果：清肝益气降压方和针刺治疗方法均能降低血压,最佳治疗方案为方＋太溪＋太冲。结论：针刺和方药对各项指标的影响程度不一,可能这种多靶点、多途径、多层次的作用方式,是针药产生协同作用的基本原因。针刺和药物可以按照中医辨证施治原则配伍使用。     

基于深度表示的中医病历症状表型命名实体抽取研究

目的：命名实体识别在自然语言处理中是最基本的任务之一,本文通过应用深度表示的方法实现临床上的现病史数据的自动标识。方法：本文随机选取了10 426条现病史句子作为主要的文本研究对象,分别用词嵌入（word2vec）和网络结构特征（node2vec）两种构建向量的方法生成不同的词向量特征,再在基于条件随机场（Conditional Random Field,CRF）和结构化支持向量机（Structured Support Vector Machines,SSVM）的方法上进行十重交叉验证,计算并比较基于深度表示的症状表型命名实体抽取的性能。结果：传统的CRF算法的三个评价指标（准确率,召回率,F 值）为（0.888 9,0.786 9,0.834 8）;基于WENER方法下的CRF和SSVM的评价指标为（0.975 0,0.984 9,0.979 8）和（0.992 8,0.988 9,0.990 8）;在GENER方法下基于词的CRF和SSVM算法的三个评价指标为（0.972 8,0.976 8,0.975 2）和（0.983 3,0.974 5,0.978 8）;GENER方法下基于字的CRF和SSVM算法的评价指标为（0.927 8,0.862 8,0.887 9）和（0.943 7,0.946 8,0.941 3）。结论：深度表示的命名实体抽取算法性能要比传统的非深度表示的命名实体标识算法性能好。另外,通过比较深度表示的两种算法的性能后发现,无论是基于word2vec生成的词向量还是基于node2vec生成的词向量,SSVM模型算法性能均优于CRF算法的性能。     

Are synthetic clinical notes useful for real natural language processing tasks: A case study on clinical entity recognition

Objective: Developing clinical natural language processing systems often requires access to many clinical documents, which are not widely available to the public due to privacy and security concerns. To address this challenge, we propose to develop methods to generate synthetic clinical notes and evaluate their utility in real clinical natural language processing tasks.Materials and Methods: We implemented 4 state-of-the-art text generation models, namely CharRNN, SegGAN, GPT-2, and CTRL, to generate clinical text for the History and Present Illness section. We then manually annotated clinical entities for randomly selected 500 History and Present Illness notes generated from the best-performing algorithm. To compare the utility of natural and synthetic corpora, we trained named entity recognition (NER) models from all 3 corpora and evaluated their performance on 2 independent natural corpora.Results: Our evaluation shows GPT-2 achieved the best BLEU (bilingual evaluation understudy) score (with a BLEU-2 of 0.92). NER models trained on synthetic corpus generated by GPT-2 showed slightly better performance on 2 independent corpora: strict F1 scores of 0.709 and 0.748, respectively, when compared with the NER models trained on natural corpus (F1 scores of 0.706 and 0.737, respectively), indicating the good utility of synthetic corpora in clinical NER model development. In addition, we also demonstrated that an augmented method that combines both natural and synthetic corpora achieved better performance than that uses the natural corpus only.Conclusions: Recent advances in text generation have made it possible to generate synthetic clinical notes that could be useful for training NER models for information extraction from natural clinical notes, thus lowering the privacy concern and increasing data availability. Further investigation is needed to apply this technology to practice.     

伤安素(OUR)在大面积烧伤微粒皮移植异种皮覆盖的临床观察

目的观察伤安素碳纤维敷料对大面积深度烧伤切痂微粒皮移植异种皮覆盖的治疗作用。方法选择50%TBSA以上深度烧伤患者76例,分为对照组(碘伏纱布,棉垫包扎)和治疗组(伤安素碳纤维敷料,棉垫包扎),创面深度均为Ⅲ度切痂创面,观察面积为30%～51%[(31±4.6)%];创面处理时间:手术部位24 h内0.5%碘伏包扎,每日换药1次。手术切痂时间:治疗组伤后5～7 d[(5.80±0.14)d],对照组伤后5～7 d[(5.71±0.21)d],非手术部位全部用SD-Ag暴露和烤架促进成痂,观察渗出情况、异种皮排异时间、残余创面炎症反应、创面愈合时间、创面愈合质量。结果治疗组吸收容量大,异种皮排异时间较对照组平均延长4.76 d,残余创面炎症反应轻,创面愈合时间较对照组平均缩短5.80 d。结论伤安素碳纤维敷料具有吸水性强、可抑制细菌生长、延长异种皮排异时间、促进创面愈合、减少瘢痕形成等优点。     

De-identification of unstructured paper-based health records for privacy-preserving secondary use

Whenever personal data is processed, privacy is a serious issue. Especially in the document-centric e-health area, the patients’ privacy must be preserved in order to prevent any negative repercussions for the patient. Clinical research, for example, demands structured health records to carry out efficient clinical trials, whereas legislation (e.g. HIPAA) regulates that only de-identified health records may be used for research. However, unstructured and often paper-based data dominates information technology, especially in the healthcare sector. Existing approaches are geared towards data in English-language documents only and have not been designed to handle the recognition of erroneous personal data which is the result of the OCR-based digitization of paper-based health records.     

素字中医生物形象内分泌系信息破释

中医文化第一部经典《素问》,素是什么?问在其中。《博雅》曰:"素,本也"。历代医家对素字说法空也,白也,女也,与文字创作不相一致。本文对素以解剖式认读,发现素字的生物信息,贯穿着人体三焦,气化,经络,三阳会首,聚气风府,三阳开泰,永垂不朽。文字形象信息折射出生物形象信号,构成现代医学内分泌系统全部。如此中医外史的脑的文化,中医放弃继承,实在可惜。故作者不揣丑陋,书写成章,供研究中医文化的同仁,给予商榷、质疑、斧正。只有争鸣,才得医理。人云亦云,错中传误,无益中医与时俱进之发展。     

挂针为主配合拔罐治疗顽固性面肌痉挛

目的：观察挂针为主配合拔罐治疗顽固性面肌痉挛方法及临床疗效。方法：48例患者随机分为治疗组16例和对照组总32例（对照组1,2各16例），治疗组用挂针为主配合拔罐，对照组1用常规取穴及针刺手法配合拔罐；对照组2用常规取穴及针刺手法。结果：治疗组总有效率93．8％，对照组总有效率65．6％，治疗组疗效明显优于对照组（P〈0．05）。结论：挂针为主配合拔罐为临床治疗顽固性面肌痉挛较有效的方法之一，为进一步研究挂针为主配合拔罐治疗顽固性面肌痉挛提供了临床依据。