### Table 2. Comorbid Conditions at Time of Cardiac Care Unit Admission

"... In PAGE 2: ...P= .18). After subsequent removal of those patients who spent less than 24 hours in the CCU, 524 remained in the usual care group and 466 in the prayer group. Comorbid conditions upon admission were similar for each group ( Table2 ). Men and women were equally represented in the usual care and prayer groups (66% vs 61% men, respectively; P = .... In PAGE 3: ... A difference with a 2-tailed P,.05 was ac- cepted as statistically significant, except for comorbid con- ditions upon admission ( Table2 ) and individual events/ procedures occurring during the CCU stay (Table 3). For these 2 data sets, P,.... ..."

### Table VII. Reclassification of principal diagnosis codes for use with National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey data

1998

### Table 3 de nes the Care types used in this paper. Care type data structure mathematical set

1995

"... In PAGE 12: ... Table3 : Care types used in this paper. 3 Fragment speci cations 3.... ..."

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### Table 3: Optimal parameters and the smallest data-set with all the unique patterns

"... In PAGE 5: ... For ve of the ten benchmarks stud- ied, all the unique patterns observed using the refer- ence data-set are also seen using the train data-set. Table3 lists the optimal parameters and the smallest usable data-set for each benchmark. Once the samples for each benchmark are identi- ed, we select only a few dominant patterns for simu- 1 2 3 4 5 0.... ..."

### Table 1: Minimizing parameters The corresponding minimal sums of squares divided by the number of data n are given in Table 2.

1991

"... In PAGE 15: ... Starting from an initial estimate for the parameters, the algorithm converges to a local minimum. A systematic search with a variety of initial estimates and the use of graphics indicates that in all examples the numbers listed in Table 2 with corresponding parameters in Table1 are the unique global minima of SSQ. In one case, for (OSCIL) and the hardwall data, a second local minimum 103 SSQ=n = 4:5075 is located at m = ?1708:4; d = 9:3346; k = ?15384: Considering (IMPED), a simple algebraic argument shows that the gradient of SSQ with respect to the two real parameters (Re ; Im ) 2 R2 vanishes if and only if Re R = P Re Rj=n and ImR = P ImRj=n: Thus, to get the optimal least-squares t for (IMPED), we compute the mean values of Re Rj and ImRj and then according... In PAGE 16: ...593 Table 2: Residual sum of squares The experimental data (measured re ection coe cients - real and imaginary parts - as a function of frequency) are represented by solid lines in Figures 2 - 5 for hardwall, free radiation, wedge and foam terminations, respectively. The re ection co- e cients corresponding to the models with boundary conditions (OSCIL), (ELAST), (IMPED) evaluated at the optimal parameters given in Table1 are plotted in each gure by dashed, dotted, dashed-dotted lines, respectively.... ..."

### Table 1n3a Minimizing parameters

1991

"... In PAGE 15: ... Starting from an initial estimate for the parametersn2c the algorithm converges to a local minimum. A systematic search with a variety of initial estimates and the use of graphics indicates that in all examples the numbers listed in Table 2 with corresponding parameters in Table1 are the unique global minima of SSQ. In one casen2c for n28OSCILn29 and the hardwall datan2c a second local minimum 10 3 n02SSQn3dn n3d4n3a5075 is located at m n3d n001708n3a4n3bd n3d9n3a3346n3bk n3dn0015384n3a Considering n28IMPEDn29n2c a simple algebraic argument shows that the gradientof SSQ with respect to the two real parameters n28Re n10n3bImn10n29 2 R... In PAGE 16: ...593 Table 2n3a Residual sum of squares The experimental data n28measured ren0dection coen0ecients n2d real and imaginary parts n2d as a function of frequencyn29 are represented by solid lines in Figures 2 n2d 5 for hardwalln2c free radiationn2c wedge and foam terminationsn2c respectively. The ren0dection con2d en0ecients corresponding to the models with boundary conditions n28OSCILn29n2c n28ELASTn29n2c n28IMPEDn29 evaluated at the optimal parameters given in Table1 are plotted in each n0cgure by dashedn2c dottedn2c dashedn2ddotted linesn2c respectively.... ..."

### Table 2 Differentiation of controlled and uncontrolled donation after cardiac death (DCD)

"... In PAGE 4: ... Although both controlled and uncontrolled situations are ethically appropriate, in this article, we pri- marily focus on controlled DCD, which is the preference covered in the critical pathway for DCD of the Organ Procurement and Transplan- tation Network/United Network for Organ Sharing. Table2 compares and contrasts key elements of both controlled and uncontrolled DCD. Critical Pathway for DCD In 2001, the critical care advisory council of the Organ Procurement and Transplantation Network/United Network for Organ Sharing developed a critical pathway for DCD.... ..."

### Table 2: Diagnosis accuracy of some frequently used data analysis methods.

2005

"... In PAGE 6: ...erns the accuracy of diagnosis and prognosis, i.e. the proportion of correctly classifled points in randomly generated sets of \new quot; points. In order to present some information about the diagnostic accuracy of various data anal- ysis methods, we present in Table2 the results obtained by using the methods of Support Vector Machines (SVM), Decision Trees (C4.5), Nearest Neighbors, Neural Networks (Mul- tilayer Perceptron), and the Logical Analysis of Data (LAD).... ..."

### Table 1. Extraction methods and laboratory set-up of participants.

2004

"... In PAGE 4: ...bility of each laboratory to carry out the practical analysis. Each laboratory was provided with an interpretation sheet to record their results and a questionnaire to pro- vide information about the extraction and amplification procedures used; the responses are detailed in Table1 . In total, 15 data sets were reported for round 1 and 13 in round 2, comprising 2 from independent internal analysts and the remainder from independent external laborato- ries.... In PAGE 6: ...ceived by the laboratory, enabling corrective action to be taken. All but two of the participating laboratories used a commercial DNA extraction or clean-up reagent set to perform the sample extraction in round 1, and only one laboratory in round 2 used an in-house extraction method ( Table1 ). The majority of reagents chosen were suitable for extraction of bacterial genomic DNA from cell suspen- sion.... In PAGE 6: ... conclusions This scheme has highlighted several common analytical problems encountered by a wide sector of laboratories carrying out nucleic acid-based analysis. Many of the problems encountered were general issues in molecular analysis, such as inappropriate extraction or amplification procedures, PCR inhibition or contamination, poor label- ing and/or poor quality of gel photographs, and failure to record results correctly (see Table1 in the Data Supple- ment that accompanies the online version of this article at 1558... ..."

### Table 1: Distribution of patient covariates and their relationship to 30-day mortality and frequency of undergoing catheterization. Data were obtained from a cohort of 3667 elderly Medicare bene - ciaries residing in Alabama discharged with a principal diagnosis of AMI in 1990. (all ICD-9-CM codes 410 except those with a 2 in the fth position) in 1987. Their work used a generalized method of moments (GMM) instrumental variable approach (Chamberlain 1987) through a two-stage least squares procedure to estimate a treatment e ect from their data. We reexamine this question in the context of our framework using a data set consisting of 3667 elderly Alabama residents admitted to an Alabama hospital in 1990 with a principal diagnosis of AMI. 3.1 Data description

1995

"... In PAGE 9: ...2. Table1 shows the distribution of patient covariates and their relationship with 30-day mortality and frequency of undergoing car- diac catheterization. Approximately 32% of the sample underwent a cardiac catheterization, with younger patients having more frequent use of the procedure.... ..."

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