_14000-JournalWatchPBPath.Rmd

# PBPath Journal Watch 

## Recent Articles from PubMed


### Analysis of Recent Pancreas Related Articles

Pancreas Journals
https://www.ncbi.nlm.nih.gov/nlmcatalog/?term=pancreas

Pathology Journals

Member List

DOI Link
PubMed Link
Journal Link
Altmetric API
Dimensions API


USCAP abstracts vs publication

Member list vs worldmap




```
{r , eval=FALSE, include=FALSE, echo=TRUE}
# load required packages
library(tidyverse)
library(knitr)
library(rstudioapi)
```

    
```
{r eval=FALSE, include=FALSE, echo=TRUE}
knitr::opts_chunk$set(
	eval = FALSE,
	message = FALSE,
	warning = FALSE,
	include = FALSE,
	tidy = TRUE
)
```



```
{r eval=FALSE, include=FALSE, echo=TRUE}
myTerm <- rstudioapi::terminalCreate(show = FALSE)
rstudioapi::terminalSend(myTerm,  esearch -db pubmed -query 'pancreas[Title/Abstract]) AND pathology' -datetype EDAT -min 2018/05/01 -max 3000 | \
efetch -format xml | \
xtract -pattern PubmedArticle -element MedlineCitation/PMID \
-block ArticleId -if ArticleId@IdType -equals doi -element ArticleId &> myquery.txt )
Sys.sleep(1)
repeat{
    Sys.sleep(0.1)
    if(rstudioapi::terminalBusy(myTerm) == FALSE){
        print( Code Executed )
        break
    }
}
```


```
{r eval=FALSE, include=FALSE, echo=TRUE}
readLines( myquery.txt )
```



Pathology Journal ISSN List was retrieved from [In Cites Clarivate](https://jcr.incites.thomsonreuters.com/), and Journal Data Filtered as follows: `JCR Year: 2016 Selected Editions: SCIE,SSCI Selected Categories: 'PATHOLOGY' Selected Category Scheme: WoS`

```
{r Get ISSN List from data downloaded from WoS 1, eval=FALSE, include=FALSE, echo=TRUE}
# Get ISSN List from data downloaded from WoS
ISSNList <- JournalHomeGrid <- read_csv( data/JournalHomeGrid.csv ,
                                        skip = 1) %>%
    select(ISSN) %>%
    filter(!is.na(ISSN)) %>%
    t() %>%
    paste( OR  , collapse =   ) # add OR between ISSN List

ISSNList <- gsub(  OR $ ,   ,ISSNList) # to remove last OR
```

Data is retrieved from PubMed via E-direct.

PubMed collection from National Library of Medicine (https://www.ncbi.nlm.nih.gov/pubmed/), has the most comprehensive information about peer reviewed articles in medicine.
The API (https://dataguide.nlm.nih.gov/) is available for getting and fetching data from the server.

The query for PubMed is generated as  ISSN List AND keywords  like done in [advanced search of PubMed](https://www.ncbi.nlm.nih.gov/pubmed/advanced).


```
{r Generate Search Formula For Pathology Journals AND Countries 1, eval=FALSE, include=FALSE, echo=TRUE}
# Generate Search Formula For Pathology Journals AND Countries
searchformulaTR <- paste( ' ,ISSNList, ' ,   AND  ,  Turkey[Affiliation] )
searchformulaDE <- paste( ' ,ISSNList, ' ,   AND  ,  Germany[Affiliation] )
searchformulaJP <- paste( ' ,ISSNList, ' ,   AND  ,  Japan[Affiliation] )
```



From the fetched data articles are grouped by country and keywords.

```
{r Articles per countries per year 1, eval=FALSE, include=FALSE, echo=TRUE}
# Articles per countries per year
tableTR <- table(YearPubmed(fetchTurkey)) %>%
    as_tibble() %>%
    rename(Turkey = n, Year = Var1)

tableDE <- table(YearPubmed(fetchGermany)) %>%
    as_tibble() %>%
    rename(Germany = n, Year = Var1)

tableJP <- table(YearPubmed(fetchJapan)) %>%
    as_tibble() %>%
    rename(Japan = n, Year = Var1)

# Join Tables
articles_per_year_table <- list(
    tableTR,
    tableDE,
    tableJP
) %>%
    reduce(left_join, by =  Year , .id =  id )

```


```
{r Prepare table for output 1, eval=FALSE, include=FALSE, echo=TRUE}
# Prepare table for output
articles_per_year <- articles_per_year_table %>%
    gather(Country, n, 2:4)

articles_per_year$Country <- factor(articles_per_year$Country,
                                    levels =c( Japan ,  Germany ,  Turkey ))
```


**Result:**


```
{r Print the Table of Articles per year per country 1, eval=FALSE, include=FALSE, echo=TRUE}
# Print the Table of Articles per year, per country
knitr::kable(articles_per_year_table, caption =  Table of Articles per year, per country )
```

mapgraph


And the figure below shows this data in a line graph.