妇癌患者的社会心理因素调查

本文以自编病前负性情绪调查表、ＬＳＥ─Ｒ及ＥＰＱ对５６例妇癌住院病人进行了调查，并以５６例内科病住院病人作对照。结果显示，６９．６％的妇癌病人在病前有负性情绪，而内科病病人只有１６．１％；８５．７％的妇癌病人病前经历了负性生活事件，而内科病组则为５８．９％；ＥＰＱ评定结果神经质分亦为前者高于后者，均提示社会心理因素与妇癌的发生密切相关。     

成年人智力发育与年龄和教育的关系

本文对韦氏成人智力量表中国修订本２５岁及其以上成年人城乡样本共１９７６人在校正各年龄组的文化程度以后，比较了年龄和教育因素对成年人智力发展的影响。结果发现：与晶体智力有关的测验成绩并不随年龄增大而下降，某些测验（如知识；领悟等）甚至呈上升趋势；与流体智力有关的测验成绩随年龄的增大而下降；而测量精神运动速度（数字符号测验）的成绩受年龄影响最为明显。看来流体－晶体智力理论能较好地解释成年人的典型智力发     

Detection of electrocardiographic ‘left ventricular strain’ using neural nets

The use of artificial neural networks for classification of ST-T abnormalities of the electrocardiogram (ECG) was investigated. A training set of 356 lateral leads selected from 105 ECGs was visually classified as exhibiting one particular ST-T morphology (left ventricular (LV) strain) or not. Selected measurements, together with the classification, were fed as input to a three-layer software-based network during the learning process. The performance of the network was evaluated by comparing the results obtained from the network with conventional criteria, using two test sets. Set 1 comprised 63 lateral leads from 32 ECGs with ST-T changes showing atypical forms of LV strain. Set 2 consisted of 80 lateral leads from 20 ECGs containing normal and abnormal T-waves. For set 1, the network outperformed conventional criteria, having a higher sensitivity (96 per cent against 85 per cent) and specificity (67 per cent against 50 per cent). With test set 2, both network and conventional criteria were 100 per cent sensitive and 100 per cent specific. For sets 1 and 2 combined, the network had a higher overall sensitivity (97 per cent agaisst 89 per cent) and specificity (88 per cent against 82 per cent). The results suggest that neural networks may be useful in selected areas of electrocardiography, but care is required when selecting patterns for use in the training process.     

New approaches to QSAR: Neural networks and machine learning

Summary Neural networks and machine learning are two methods that are increasingly being used to model QSARs. They make few statistical assumptions and are nonlinear and nonparametric. We describe back-propagation from the field of neural networks, and GOLEM from machine learning, and illustrate their learning mechanisms using a simple expository problem. Back-propagation and GOLEM are then compared with multiple linear regression (using the parameters and their squares) on two real drug design problems: the inhibition ofEscherichia coli dihydrofolate reductase (DHFR) by pyrimidines and the inhibition of rat/mouse tumour DHFR by triazines.     

Neural networks in the study of the brain

Neural networks are models of the brain and have been used within Artificial Intelligence to provide alternative explanations to the symbolic explanations of cognition in which one assumes that an intelligent system has certain explicit representations of some aspect of the world and uses these in intelligent behavior. Obviously, if neural networks are indeed good models of the brain, and give a satisfactory account of cognition, then they could be a valuable tool to neuroscientists. This article gives a brief overview of the various neural network models, and critically reviews their status as models of the brain and of cognition.     

2000—2022年人工智能应用于食管癌领域全球研究的可视化分析

背景 随着近20余年人工智能（AI）在食管癌领域应用研究的骤增,出现了许多关于该研究的系统、荟萃分析等,但其仅针对AI在该领域应用的单一方面的总结研究,研究人员难以全面了解领域最新发展与研究热点。目的 通过文献计量分析总结AI在食管癌领域的应用,阐明AI在食管癌领域相关研究的进展、热点和新兴趋势。方法检索Web of Science Core Collection(WoSCC)的Science Citation Index Expanded(SCI-E)数据库收录的AI应用于食管癌领域的所有英文文献,检索时间2000-01-01至2022-04-06。应用Microsoft Excel 2019、CiteSpace(5.8R3-64bit)和VOSviewer(1.6.18)对文献进行发文量、国家、作者、机构、共被引和关键词分析。结果 2000—2022年共检索到AI应用于食管癌领域的文献918篇,共计引用文献总量23 490篇。发文趋势：2000—2016年为迟缓期,发文量从6篇增至40篇;2017—2022年为快速增长期,发文量从62篇突增至216篇。60个国家、118家机构、5 ...     

人工智能应用于糖尿病视网膜病变的文献计量学分析

背景 近年来,人工智能（AI）在医学领域发展迅速,在糖尿病视网膜病变（DR）中的应用范围不断扩展。目的 通过文献计量分析总结AI在DR领域的应用情况,阐明AI在DR领域相关研究的现状、热点和新兴趋势,以期为未来的研究提供思路。方法 以Web of Science数据库为来源,检索建库至2022-11-04的AI应用于DR领域的相关文献,运用CiteSpace软件对纳入文献进行发文量、国家、机构、作者、共被引和关键词的文献计量学分析。结果共获得1 770篇文献,2011年1月至2022年11月发文量总体呈上升趋势,2021年发文量达峰值（402篇）。中国是发文量（440篇）位居第1的国家,英国为中心性（0.26）最高的国家。机构合作网络图谱共纳入436家机构,以中山大学和首都医科大学为代表。作者合作网络图谱共纳入601位作者,以JIA Y L和HWANG T为代表。GULSHAN V、ABRàMOFF M D与TING D W 3位高被引作者对该领域做出了重要贡献。Ophthalmology、Invest Ophth Vis Sci和Ieee T Med Imaging是AI应用于DR领...     

Emotional reactivity and sympatho-adrenal activity in the rat (author's transl)

Using the open-field test, differences in emotional reactivity were shown in male rats of several albino strains. These behavioural differences were then investigated in relation to physiological differences. It was found that, under resting conditions, sympatho-adrenomedullary activity as estimated by urinary catecholamine excretion and adrenal catecholamine content is lower in the more emotionally reactive rats. The resting heart rate is correspondingly slower in these animals though they show the same noradrenaline cardiac concentration as the nonreactive rats. These data suggest that high defecating rats in the open-field exhibit a lower sympathetic tonus, possibly linked, however, with a higher parasympathetic tonus.     

Cognitive and motor skills in achondroplastic infants: Neurologic and respiratory correlates

Thirteen infants with achondroplasia underwent psychometric testing as part of a comprehensive neurologic assessment. As a group, mental development was average and motor development was delayed, although a wide range of scores was obtained. Foramen magnum measurements were correlated with respiratory dysfunction, abnormal so-matosensory evoked potentials, and delayed motor development. Abnormal polysomno-gram outcome was associated with reduced mental capacity. In light of the reported increased frequency of respiratory dysfunction in achondroplasia, these findings warrant careful attention and further study.     

Dialysate-side urea kinetics. Neural network predicts dialysis dose during dialysis

Determination of the adequacy of dialysis is a routine but crucial procedure in patient evaluation. The total dialysis dose, expressed as Kt/V, has been widely recognised to be a major determinant of morbidity and mortality in haemodialysed patients. Many different factors influence the correct determination of Kt/V, such as urea sequestration in different body compartments, access and cardiopulmonary recirculation. These factors are responsible for urea rebound after the end of the haemodialysis session, causing poor Kt/V estimation. There are many techniques that try to overcome this problem. Some of them use analysis of blood-side urea samples, and in recent years, on-line urea monitors have become available to calculate haemodialysis dose from dialysate-side urea kinetics. All these methods require waiting until the end of the session to calculate the Kt/V dose. In this work, a neural network (NN) method is presented for early prediction of the Kt/V dose. Two different portions of the dialysate urea concentration-time profile (provided by an on-line urea minitor) were analysed: the entire curve A and the first half B, using an NN to predict the Kt/V and compare this with that provided by the monitor. The NN was able to predict Kt/V is the middle of the 4h session (B data) without a significant increase in the percentage error (B data: 6.69%±2.46%; A data: 5.58%±8.77%, mean±SD) compared with the monitor Kt/V.