髋关节一过性滑膜炎的治疗进展

髋关节一过性滑膜炎是骨科临床上的常见病,以髋关节疼痛、活动障碍为主要症状,严重影响患者的日常生活。多年来,人们一直致力于髋关节一过性滑膜炎的治疗方法的研究,但由于其病因尚未完全明确,人们在针对不同病因的治疗探索中提出了多种不同的治疗方法,且均取得了良好的疗效。     

Semantic text classification: A survey of past and recent advances

Automatic text classification is the task of organizing documents into pre-determined classes, generally using machine learning algorithms. Generally speaking, it is one of the most important methods to organize and make use of the gigantic amounts of information that exist in unstructured textual format. Text classification is a widely studied research area of language processing and text mining. In traditional text classification, a document is represented as a bag of words where the words in other words terms are cut from their finer context i.e. their location in a sentence or in a document. Only the broader context of document is used with some type of term frequency information in the vector space. Consequently, semantics of words that can be inferred from the finer context of its location in a sentence and its relations with neighboring words are usually ignored. However, meaning of words, semantic connections between words, documents and even classes are obviously important since methods that capture semantics generally reach better classification performances. Several surveys have been published to analyze diverse approaches for the traditional text classification methods. Most of these surveys cover application of different semantic term relatedness methods in text classification up to a certain degree. However, they do not specifically target semantic text classification algorithms and their advantages over the traditional text classification. In order to fill this gap, we undertake a comprehensive discussion of semantic text classification vs. traditional text classification. This survey explores the past and recent advancements in semantic text classification and attempts to organize existing approaches under five fundamental categories; domain knowledge-based approaches, corpus-based approaches, deep learning based approaches, word/character sequence enhanced approaches and linguistic enriched approaches. Furthermore, this survey highlights the advantages of semantic text classification algorithms over the traditional text classification algorithms.     

亚急性甲状腺炎中西医治疗进展

亚急性甲状腺炎发病率虽然只有0.5~6.2%,但它会导致患者疼痛反复发作,影响患者的生活质量。临床上只有早期发现、早期诊断并进行干预才能早期治愈。文章就亚急性甲状腺炎的症状、体征及实验室检查及西医治疗,中医对该病的病因病机及治疗给予论述。