Discriminant analysis.

Discriminant analysis (DA) is a pattern recognition technique that has been widely applied in medical studies. It allows multivariate observations ("patterns" or points in multidimensional space) to be allocated to previously defined groups (diagnostic categories). The relationships between DA and other multivariate statistical techniques of interest in medical studies will be briefly discussed. The main emphasis is on linear discriminant functions (LDF). The theoretic assumptions underlying DA using LDFs will be presented, and the effect of violations to these assumptions will be reviewed in detail. Alternative methods will be presented when violations cause serious problems. It has been shown that the familiar LDF is fairly robust to departures from the assumptions. The application of the LDF in less than ideal situations therefore often does not cause much harm (if the violations are not too grotesque). Another set of problems reviewed is how to estimate the misallocation probabilities when using discriminant functions. The selection of the "best" subset of variables out of the complete set will be discussed. Practical guide lines are given based on the theoretic studies reviewed. When possible, available computer programs for various problems of DA will be indicated. The review does not aim at covering all medical studies where DA has been applied, since emphasis is on the practical conclusions of the theory of DA.     

Discriminant analysis of functional connectivity patterns on Grassmann manifold

The functional brain networks, extracted from fMRI images using independent component analysis, have been demonstrated informative for distinguishing brain states of cognitive function and brain disorders. Rather than analyzing each network encoded by a spatial independent component separately, we propose a novel algorithm for discriminant analysis of functional brain networks jointly at an individual level. The functional brain networks of each individual are used as bases for a linear subspace, referred to as a functional connectivity pattern, which facilitates a comprehensive characterization of fMRI data. The functional connectivity patterns of different individuals are analyzed on the Grassmann manifold by adopting a principal angle based Riemannian distance. In conjunction with a support vector machine classifier, a forward component selection technique is proposed to select independent components for constructing the most discriminative functional connectivity pattern. The discriminant analysis method has been applied to an fMRI based schizophrenia study with 31 schizophrenia patients and 31 healthy individuals. The experimental results demonstrate that the proposed method not only achieves a promising classification performance for distinguishing schizophrenia patients from healthy controls, but also identifies discriminative functional brain networks that are informative for schizophrenia diagnosis.     

口腔黏膜组织癌变趋势的判别

目的建立口腔黏膜组织癌变趋势的判别方法,为临床肿瘤或疑似癌变组织的早期诊断奠定研究基础。方法采用RT-PCR技术检测口腔正常组织、口腔黏膜白斑病组织（oral leukoplakia,OLK）和口腔鳞状细胞癌（oralsquamous cell carcinoma,OSCC）组织的肿瘤相关基因（NF-1,ACP-2,BCL-2,CLK-3,FKBP-8,SOCS-3,XRCC-1,CTNNB-1,GDF-15）表达水平,采用Fisher判别分析建立口腔黏膜组织癌变趋势大小的基因诊断方法,采用Cross-validated（a）法对本判别方法进行评价。结果 ACP-2,BCL-2及SOCS-3 3个基因的表达水平在3种组织间逐渐降低（P〈0.05）,而NF-1,CLK-3,FKBP-8,XRCC-1,CTNNB-1及GDF-15 6个基因的表达水平在3种组织间逐渐升高（P〈0.05）;口腔黏膜组织癌变趋势的判别公式：Y1=-16.811＋0.477 XNF-1＋0.540 XACP-2-0.543 XCTNNB-1-0.089 XSOCS-3;Y2=-35.832＋0.073 XNF-1-0.074 XACP-2＋0.306 XCTNNB-1＋0.191 XSOCS-3;判别界值〉8.6513可判定为无癌变,0.1117～8.6513为轻度癌变组织,〈0.1117为癌变组织;采用Cross-validated（a）法进行评价,总判别符合率为100%;交互判别符合率为100%,灵敏度为100%,特异度为100%。结论本研究建立了口腔黏膜组织癌变趋势判别公式,有助于其基因诊断方法的建立。     

运动单位电位多项参数对不同类别运动单位电位的判别分析

目的 探讨运动单位电位(MUP)多项参数在判定不同类别MUP中的价值。方法 选取10例肌肉病变患者、13例神经病变患者和22例正常人，采用棘波触发平均技术，获取肱二头肌、胫前肌和股内侧肌MUP的时限、波幅、面积和面积／波幅比4项参数，通过SPSS10．0软件进行方差分析和判别分析。结果 所有肌肉MUP各参数值在3组间的差异均有显著性意义(P＜0．0001)；各参数及不同参数组合对不同类别的MUP具有不同的判别率和总回代符合率。结论 时限和面积／波幅比对肌源性损害MUP均具有较强的判别能力，但时限对肌源性损害MUP的判别更具敏感性和特异性；面积和波幅对神经源性损害MUP均具有较强的判别能力，但面积对神经源性损害MUP的判别更具敏感性和特异性；多个参数组合可以提高对不同类别MUP的综合判别能力。     

Discriminant analysis of urinary calculi by near-infrared reflectance spectroscopy.

Near-infrared reflectance analysis has been used to determine the qualitative and semi-quantitative composition of urinary calculi. This simple method requires calibration of the most common urinary calculi. Analysis time is short (less than 1 min) and only very small amounts of calculus in powder form (less than 100 micrograms) are required without the use of any reagent. Moreover, when compared to infrared spectroscopy, this method provides sufficient accuracy to identify mixed calculi containing two or three components, and permits semi-quantitative determinations. The speed and simplicity of this technique makes it a powerful method for the routine analysis of urinary calculi in clinical laboratories.     

多层螺旋CT血管造影对胡桃夹综合征的判别分析

目的:用多层螺旋CT血管造影(MSCTA)诊断胡桃夹综合征(NCS),探讨MSCTA诊断NCS的指标。方法:利用16排MSCTA测量24例NCS患者卧位状态下肠系膜上动脉(SMA)与腹主动脉(AO)之间的角度和左肾静脉(LRV)内径,并和对照组作比较。结果:24例NCS患者SMA与AO夹角A’的平均值为16.46°±3.41°。LRV穿过夹角处的前后径为(0.31±0.12)cm。对照分析NCS组和正常组的LRV穿过SMA夹角处狭窄段及其左侧扩张段的前后径、前后径比、截面积比以及SMA夹角A、A’、左右肾的体积差、体质量指数等8项指标,除了LRV扩张段的前后径外,其余7项指标均有显著性差异。对上述8项指标作判别分析得出判别方程为:D=-2.543-0.743x1+0.046x6+0.142x8。结论:MSCTA能清楚的显示LRV周围的解剖结构,对NCS有重要的诊断价值。     

大脑前额叶多通道近红外光谱信号数据的分类鉴别

背景：精神分裂症主要是通过症候学的方法进行诊断,近年来通过神经影像技术与模式识别的结合对精神分裂症患者与正常人进行鉴别的研究已经引起人们的兴趣。 目的：利用模式识别的方法对精神分裂症患者和正常人的大脑前额叶多通道近红外光谱信号数据进行分类鉴别,验证其可行性。 方法：使用言语流畅性测验作为激活任务,采集精神分裂症患者和正常人的大脑前额叶的近红外光谱信号数据。对采集数据进行预处理后计算各通道均值作为特征,计算接收者操作特征的曲线下方面积对通道特征进行分类性能排序,使用支持向量机按性能排序的特征组合做分类,然后用留一验证法计算分类性能指标,验证分类能力。 结果与结论：研究发现特征性能排序前8位的特征组合的准确度最高达到95.24%,并且这8个通道都位于右侧前额叶。推断右侧前额叶区域可能是影响精神分裂症患者的主要脑区,因此根据结果可以推断出近红外光谱数据通过与模式识别方法的结合可以成为辅助诊断精神分裂症病患者的一种手段。     

Discriminant analysis of laboratory tests in patients admitted to a coronary care unit

Discriminant analysis of chemistry and hematology laboratory test results was used to classify patients with and without myocardial infarction in a coronary care unit. We studied 64 patients with myocardial infarction and 70 patients without infarction, using logistic regression, linear and quadratic discriminant analyses on untransformed and logarithmically transformed data. Serum aspartate aminotransferase (AST, EC 2.6.1.1), the best single discriminating test, classified 73% of patients correctly. Quadratic discriminant analysis on log-transformed data had a 98.5% classification accuracy when all variables were used in the discriminant function and had the highest classification accuracy and precision. All of the discriminant methods had acceptable cross-validation.     

Discriminant analysis of ultrasonic texture data in diffuse alcoholic liver disease: 1. Fatty liver and cirrhosis

In previous work by our group, it has been shown that the use of texture analysis on digitally recorded radio-frequency ultrasonic signals can provide useful diagnostic information in diffuse liver disease. A rigorous multivariate analysis and the addition of new texture parameters has confirmed the efficacy of the technique. Discriminant functions have been produced to provide excellent accuracies in the detection of diffuse liver disease.     

Discriminant functions in differential diagnosis of hypercalcemic patients

Using readily available biochemical assays of plasma and urine constituents, we have defined discriminant functions useful as a guide to the differential diagnosis of patients with hypercalcemia. The decreasing rank order of contribution of the variables to the discriminant functions was as follows: plasma albumin, plasma phosphate, plasma chloride, log10 (calcium excretion per liter of glomerular filtrate), and log10 (plasma gamma-glutamyltransferase). Discriminant functions have been defined for patients with values for plasma creatinine above and below 185 mumol/L, and for practical conditions in which plasma and urine samples, or plasma samples only, are available.     

Discriminant snakes for 3D reconstruction of anatomical organs

In this work a new statistic deformable model for 3D segmentation of anatomical organs in medical images is proposed. A statistic discriminant snake performs a supervised learning of the object boundary in an image slice to segment the next slice of the image sequence. Each part of the object boundary is projected in a feature space generated by a bank of Gaussian filters. Then, clusters corresponding to different boundary pieces are constructed by means of linear discriminant analysis. Finally, a parametric classifier is generated from each contour in the image slice and embodied into the snake energy-minimization process to guide the snake deformation in the next image slice. The discriminant snake selects and classifies image features by the parametric classifier and deforms to minimize the dissimilarity between the learned and found image features. The new approach is of particular interest for segmenting 3D images with anisotropic spatial resolution, and for tracking temporal image sequences. In particular, several anatomical organs from different imaging modalities are segmented and the results compared to expert tracings.     

基于链式方程填补的前列腺癌logistic判别分析

目的应用基于链式方程的填补方法处理医学研究中的数据缺失,并以填补后完全数据构建联合指标的logistic判别函数,判断其在前列腺癌的预测诊断中的应用价值。方法采用模拟研究,针对现实数据缺失情况模拟不同填补集结果,并以此对现实数据进行填补,以完整数据构建logistic判别,进行分析预测。结果填补结果随着填补次数的增加而逐渐接近真实值并趋于稳定。联合年龄、血清前列腺特异性抗原值、血流阻力指数及经直肠前列腺超声检查指标的logistic判别分析结果的灵敏度为82.39%,特异度为74.86%。结论联合指标分析可提高前列腺癌的诊断预测水平,以减轻患者穿刺痛苦。     

Discriminant ability and criterion validity of the Trunk Impairment Scale for cerebral palsy

Aims: To compare the performance of children with mild and moderate-to-severe cerebral palsy (CP) on the Trunk Impairment Scale (TIS), Gross Motor Function Measure (GMFM), and on center-of-pressure variables; to establish the discriminant ability of these tools to predict severity of motor impairment in CP; and to investigate the criterion validity of the TIS.

Methods: Children with mild (n?=?18, 11 males, 7 females, mean age?=?9.5?±?2.9 years, Gross Motor Function Classification System I–II) and moderate-to-severe (n?=?18, 11 males, 7 females, mean age?=?9.2?±?229, Gross Motor Function Classification System III–IV) CP were tested using the TIS and the GMFM, and during static sitting on force-plate.

Results: Children with mild CP showed better trunk (median; 95% confidence interval?=?22.5; 21.29–22.59 vs. 13; 11.97–14.8; p?<?0.001) and gross motor (60; 57.73–59.3 vs. 40; 38.96–46.25; p?<?0.001) scores, and better postural control (lower center of pressure (CoP) displacement [anterior–posterior: (0.42; 0.32–1.11 vs. 0.89; 0.70–1.65; p?=?0.022); medial–lateral: (0.42; 0.31–1.08 vs. 0.91; 0.65–1.17; p?=?0.044)], and lower area of sway, (0.05; ?0.15–0.97 vs. 0.44; 0.23–0.90; p?=?0.008) than the moderate-to-severe group. Trunk control and gross motor function explained 81.5% of the variance in the severity of motor condition. Correlations between the TIS and the GMFM were excellent (ρ?=?0.944, p?<?0.001); correlations between the TIS and CoP variables were low (anterior–posterior displacement: ρ?=??0.411, p?<?0.05; medial–lateral displacement: ρ?=??0.327, p?<?0.05); area of sway: ρ?=??0.430, p?<?0.05; velocity of sway: ρ?=??0.308, p?<?0.05).

Conclusions: The TIS is able to differentiate levels of trunk control across various levels of motor impairments in CP. It is a valid tool to assess trunk control, showing very high concurrent validity with the GMFM sitting dimension.

• Implications for Rehabilitation

• Trunk Impairment Scale (TIS) can be used by rehabilitation professionals to differentiate levels of trunk control across levels of motor impairment.

• TIS showed concurrent validity with Gross Motor Function Measure and should be used to assess trunk control in children with cerebral palsy (CP) in clinical settings.

• The use of TIS allows a reliable assessment of postural control in children with CP in clinical settings.

     

Discriminant value of automated leucocyte VCS parameters in the detection of tropical infections

IntroductionIn India, infectious diseases are a leading treatable cause of morbidity and mortality. Mangalore being endemic to many vector‐borne diseases, their incidence is known to show seasonal variations with sharp increase during monsoon. Leucocytes have substantial role in the immunological pathogenesis of infections.MethodsThe present series was a hospital‐based cross‐sectional study performed in a tertiary care hospital for a period of three months from June‐August wherein the cell population data of cases of malaria, dengue, leptospirosis, typhoid and rickettsial infections along with equal number of healthy controls were collected and analysed. Effectiveness of leucocyte‐related volume (V), conductivity (C) and scatter (S) parameters by Coulter®DXH800 haematology analyser in predicting these infections was appraised.ResultsA total of 324 cases comprising of malaria (50%), dengue (30.9%), leptospirosis (13.9%), typhoid (4.0%) and rickettsial infections (1.2%) were included. There was statistically significant differences (P < 0.05) in the mean values of complete blood count parameters—haemoglobin, total leucocyte count, red blood cell count, haematocrit, red cell distribution width, differential leucocyte count, platelet count and plateletcrit between cases and controls and also between specific infections. The mean volumes of neutrophil, monocyte and lymphocyte were considerably increased in malaria and dengue fever compared to leptospirosis, typhoid and rickettsial infections. VCS parameters were the least altered in typhoid fever, except for a strikingly high conductivity and scatter of eosinophils.ConclusionsHaematological analysis is a part of routine evaluation of any case of febrile illness. This study showed that there are specific alterations in VCS parameters in different types of infections such as malaria, dengue, leptospira, typhoid and rickettsia, the information and analysis of which comes without any additional cost.     

冠心病患者运动试验Bayes准则模型的应用

本文采用无创性Bayes准则多元逐步判别分析方法,对73例同期接受改良Bruce方案平板运动试验及选择性冠状动脉造影对照的住院病人,进行回顾性资料处理(SAS/PC 6.03版微机软件系统),并将所建立的拟合模型对29例患者进行前瞻性研究.结果显示该多变量分析方法在建立良好的预测模型和判定指标的筛选方面具有独特价值,提示多变量分析方法可显著提高运动试验诊断冠心病的敏感性和特异性.     

Discriminant effects of behaviorally active and inactive analogs of phencyclidine on membrane electrical excitability

The discriminant effects of several behaviorally active and inactive analogs of phencyclidine [PCP; 1-(phenylcyclohexyl) piperidine] and the actions of PCP and three Ca-channel antagonists were examined on electrical excitability in frog and crayfish skeletal muscles. In frog sartorius muscle, 1-[1-(2-thienylcyclohexyl)piperidine (TCP; 100 microM), a behaviorally active analog of PCP, increased action potential duration nearly 9-fold, blocked delayed rectification and at 0.5 to 1 microM also increased the quantal release of transmitter. A partial blockade of delayed rectification and slight prolongation of the action potential occurred with 1-(p-fluorophenylcyclohexyl)piperidine (p-F-PCP; 100 microM), which possesses about 25% of the behavioral activity of PCP. Of the remaining p-phenyl- substituted analogs which never exhibited more than 10% of the behavioral potency of PCP, only 1-(1-p-nitrophenylcyclohexyl)piperidine (p-NO2-PCP; 100 microM) produced a frequency-dependent prolongation of the action potential but, like the p-methoxy-, p-chloro- and p-methyl- analog, it did not block delayed rectification. The order of potencies of these analogs in blocking delayed rectification, prolonging the muscle action potential and in affecting alternation impairment and response rate depression is therefore: PCP much greater than TCP greater than p-F-PCP much greater than p-CH3-PCP = p-CH3O-PCP = p-Cl-PCP = p-NO2-PCP. Like PCP and its behaviorally active analogs, verapamil (50 microM) and bepridil (50 microM), two Ca-channel blockers, also blocked delayed rectification in frog sartorius muscles whereas nifedipine (50 microM), another Ca-channel blocker, did not.(ABSTRACT TRUNCATED AT 250 WORDS)