Publications by Developed by the Computational Medicine Lab for Carlos Cárdenas, PLESS.
Cole Laparo vs Robotic
The following results are a complementary analysis for Juan Quispe’s project. OR time through the years Procedure time through the years Mean of Age by Groups Distribution of gender by group Data in Tables OR Time ## [1] "Mean of or_time for Laparoscopic: 122" ## [1] "SD of or_time for Laparoscopic: 38" ## [1] "Mean of or_time for Robotic...
265 sym R (560 sym/12 pcs)
Análisis Preliminares
Cargando los datos Revisando escalas por variable La escala de cada variable debe coincidir con el codebook provisto. Variable folio_sel character folio character code_upm character ponde_f numeric sexo numeric edad numeric rural numeric intp numeric dias1 numeric gpo_diversidad1 numeric recomendable1 numeric dias2 numer...
6744 sym
HbA1c Project
1. On average, how much did HbA1c levels decreased at the 1-month, 3-months and 1-year cohorts? The first step is to evaluate the amount of missing values per cohort in the data set, this will allow us to asses the strength of evidence visualized comparing HbA1c levels between postoperative cohorts (1-month, 3-months, 6-months, 1-year). Variabl...
2642 sym R (839 sym/3 pcs) 1 img
Bariatric Sx- Smoking Project
The following tables are arranged in order to facilitate the interpretation of the data generated in the project. The name of the variables have been modified to make the coding process easier, nevertheless an effort was made to keep them understandable. There is a total of 835 patients in this data set. Smokers in the population smoke_labels ...
5724 sym R (12481 sym/69 pcs) 23 tbl
Culinary Medicine
Gemeralidades de los Datos Exploración de datos faltantes Variables categóricas Variables pre y post Las siguientes variables NO han sido consideradas en el análisis por las razones que se exlpican en cada caso: Cuál crees que es la razón por la aumentaron/disminuyeron tus horas de cocinado en casa? Solo hay una respuesta en algunos cas...
982 sym 7 img
pepeProject1
Variables y valores disponibles ## tibble [611 × 17] (S3: tbl_df/tbl/data.frame) ## $ SUJETO : num [1:611] 1 2 3 4 5 6 7 8 9 10 ... ## $ UNIVERSIDAD : Factor w/ 4 levels "UM","UNAV","ULSA",..: 1 1 1 1 1 1 1 1 1 1 ... ## $ EDAD : num [1:611] 18 21 18 21 18 18 22 18 21 18 ... ## $ SEXO : Facto...
1093 sym R (1492 sym/1 pcs) 12 img 24 tbl
Bio-Math-Vaccine
Generalidades Características Iniciales rows 1535 columns 38 discrete_columns 37 continuous_columns 1 all_missing_columns 0 total_missing_values 7498 complete_rows 30 total_observations 58330 memory_usage 390648 Visualización de las Características Iniciales Visualización de la distribución de las variables categóricas ...
1107 sym 16 img 1 tbl
Proyecto Tirsa
Características Preliminares Características de Partida rows columns discrete_columns continuous_columns all_missing_columns total_missing_values complete_rows total_observations 50 50 36 14 0 0 50 2500 Visualización de Variables Categóricas Visualización de Variables Numéricas Descripción Estadística de la Demografía...
708 sym 7 img 3 tbl
Vacunas Percepción Revisiones
Summary Table Variables N No, N = 1051 Yes, N = 1,2111 p-value2 Género 1,283 0.009 Hombre 28 (28%) 493 (42%) Mujer 72 (71%) 686 (58%) Otro 0 (0%) 1 (<0.1%) Prefiero no decir 1 (1.0%) 2 (0.2%) Unknown 4 29 Edad 1,316 <18 años 0 (0%) 0 (0%) 18 a 24 años 9 (8.6%) 283 (23%) 25 a 34 años 25 (24%) 363 (30%) 35 a 44 años 36 (3...
47 sym 2 tbl
Incidentaloma
Sociodemographic variables Total(N=120) Age Mean (SD) 58.3 (14.5) Median [Min, Max] 59.0 [18.0, 89.0] Sex Female 85 (70.8%) Male 35 (29.2%) Race White 96 (80.0%) Black/African-American 10 (8.3%) American Indian/Alaska Native 2 (1.7%) Native Hawaiian/Pacific Islander 1 (0.8%) Asian 5 (4.2%) Other 4 (3.3%) Missing 2 (1.7%) Ethnicity...
2829 sym R (9551 sym/7 pcs) 13 img 6 tbl