Pipe operator

Description

See magrittr::%>% for details.

Usage

lhs %>% rhs

Arguments

Value

Returns rhs(lhs).

This function binds columns containing either the lemma of the entity or the UMLS concept unique identifier (CUI) with frequencies to a data frame. The resulting data frame can be used to train a machine learning model or for additional feature selection.

Description

This function binds columns containing either the lemma of the entity or the UMLS concept unique identifier (CUI) with frequencies to a data frame. The resulting data frame can be used to train a machine learning model or for additional feature selection.

Usage

bind_clinspacy(
  clinspacy_output,
  df,
  cs_col = NULL,
  df_id = NULL,
  subset = "is_negated == FALSE"
)

Arguments

Value

A data frame containing the original data frame as well as additional column names for each lemma or UMLS concept unique identifer found with values containing frequencies.

Examples

## Not run: 
mtsamples <- dataset_mtsamples()
mtsamples[1:5,] %>%
  clinspacy(df_col = 'description') %>%
  bind_clinspacy(mtsamples[1:5,])

## End(Not run)

This function binds columns containing entity or concept embeddings to a data frame. The entity embeddings are derived from the scispacy package, and the concept embeddings are derived from the dataset_cui2vec_embeddings dataset included with this package.

Description

The embeddings are derived from Andrew Beam's cui2vec R package.

Usage

bind_clinspacy_embeddings(
  clinspacy_output,
  df,
  type = "scispacy",
  df_id = NULL,
  subset = "is_negated == FALSE"
)

Arguments

Details

Citation

Beam, A.L., Kompa, B., Schmaltz, A., Fried, I., Griffin, W, Palmer, N.P., Shi, X., Cai, T., and Kohane, I.S.,, 2019. Clinical Concept Embeddings Learned from Massive Sources of Multimodal Medical Data. arXiv preprint arXiv:1804.01486.

License

The cui2vec data is made available under a CC BY 4.0 license. The only change made to the original dataset is the renaming of columns.

Value

A data frame containing the original data frame as well as the concept embeddings. For scispacy embeddings, this returns 200 columns of embeddings. For cui2vec embeddings, this returns 500 columns of embedings. The resulting data frame can be used to train a machine learning model.

Examples

## Not run: 
mtsamples <- dataset_mtsamples()
mtsamples[1:5,] %>%
  clinspacy(df_col = 'description', return_scispacy_embeddings = TRUE) %>%
  bind_clinspacy_embeddings(mtsamples[1:5,])

## End(Not run)

This is the primary function for processing both data frames and character vectors in the clinspacy package.

Description

This is the primary function for processing both data frames and character vectors in the clinspacy package.

Usage

clinspacy(
  x,
  df_col = NULL,
  df_id = NULL,
  threshold = 0.99,
  semantic_types = c(NA, "Acquired Abnormality", "Activity", "Age Group",
    "Amino Acid Sequence", "Amino Acid, Peptide, or Protein", "Amphibian",
    "Anatomical Abnormality", "Anatomical Structure", "Animal", "Antibiotic", "Archaeon",
    "Bacterium", "Behavior", "Biologic Function", "Biologically Active Substance",
    "Biomedical Occupation or Discipline", "Biomedical or Dental Material", "Bird",
    "Body Location or Region", "Body Part, Organ, or Organ Component",
    "Body Space or Junction", "Body Substance", "Body System", "Carbohydrate Sequence",  
       "Cell", "Cell Component", "Cell Function", "Cell or Molecular Dysfunction",
    "Chemical", "Chemical Viewed Functionally", "Chemical Viewed Structurally",
    "Classification", "Clinical Attribute", "Clinical Drug", "Conceptual Entity",
    "Congenital Abnormality", "Daily or Recreational Activity", "Diagnostic Procedure",
    "Disease or Syndrome", "Drug Delivery Device", "Educational Activity",
    "Element, Ion, or Isotope", "Embryonic Structure", "Entity",
    "Environmental Effect of Humans", "Enzyme", "Eukaryote",      "Event",
    "Experimental Model of Disease", "Family Group", "Finding", "Fish", "Food",
    "Fully Formed Anatomical Structure", "Functional Concept", "Fungus",
    "Gene or Genome", "Genetic Function", "Geographic Area",
    "Governmental or Regulatory Activity", "Group", "Group Attribute",
    "Hazardous or Poisonous Substance", "Health Care Activity",
    "Health Care Related Organization", "Hormone", "Human",
    "Human-caused Phenomenon or Process", "Idea or Concept", "Immunologic Factor",
    "Indicator, Reagent, or Diagnostic Aid",      "Individual Behavior",
    "Injury or Poisoning", "Inorganic Chemical", "Intellectual Product",
    "Laboratory or Test Result", "Laboratory Procedure", "Language", "Machine Activity",
    "Mammal", "Manufactured Object", "Medical Device",
    "Mental or Behavioral Dysfunction", "Mental Process",
    "Molecular Biology Research Technique", "Molecular Function", "Molecular Sequence",
    "Natural Phenomenon or Process", "Neoplastic Process",
    "Nucleic Acid, Nucleoside, or Nucleotide", "Nucleotide Sequence",
    "Occupation or Discipline",      "Occupational Activity", "Organ or Tissue Function",
    "Organic Chemical", "Organism", "Organism Attribute", "Organism Function",
    "Organization", "Pathologic Function", "Patient or Disabled Group",
    "Pharmacologic Substance", "Phenomenon or Process", "Physical Object",
    "Physiologic Function", "Plant", "Population Group",
    "Professional or Occupational Group", "Professional Society", "Qualitative Concept",
    "Quantitative Concept", "Receptor", "Regulation or Law", "Reptile",
    "Research Activity", "Research Device",      "Self-help or Relief Organization",
    "Sign or Symptom", "Social Behavior", "Spatial Concept", "Substance",
    "Temporal Concept", "Therapeutic or Preventive Procedure", "Tissue", "Vertebrate",
    "Virus", "Vitamin"),
  return_scispacy_embeddings = FALSE,
  verbose = TRUE,
  output_file = NULL,
  overwrite = FALSE
)

Arguments

Value

If output_file is NULL (the default), then this function returns a data frame containing the UMLS concept unique identifiers (cui), entities, lemmatized entities, CyContext negation status (TRUE means negated, FALSE means *not* negated), other CyContext contexts, and section title from the clinical sectionizer. If output_file points to a file name, then the name of the created file will be returned.

Examples

## Not run: 
clinspacy('This patient has diabetes and CKD stage 3 but no HTN.')

clinspacy(c('This pt has CKD and HTN', 'Pt only has CKD but no HTN'))

data.frame(text = c('This pt has CKD and HTN', 'Diabetes is present'),
           stringsAsFactors = FALSE) %>%
  clinspacy(df_col = 'text')

if (!dir.exists(rappdirs::user_data_dir('clinspacy'))) {
  dir.create(rappdirs::user_data_dir('clinspacy'), recursive = TRUE)
  }

clinspacy(c('This pt has CKD and HTN', 'Has CKD but no HTN'),
  output_file = file.path(rappdirs::user_data_dir('clinspacy'),
                          'output.csv'),
  overwrite = TRUE)

## End(Not run)

Initializes clinspacy. This function is optional to run but gives you more control over the parameters used by scispacy at initiation. If you do not run this function, it will be run with default parameters the first time that any of the package functions are run.

Description

Initializes clinspacy. This function is optional to run but gives you more control over the parameters used by scispacy at initiation. If you do not run this function, it will be run with default parameters the first time that any of the package functions are run.

Usage

clinspacy_init(
  miniconda = TRUE,
  use_linker = FALSE,
  linker_threshold = 0.99,
  ...
)

Arguments

Value

No return value.

Cui2vec concept definitions

Description

This dataset contains definitions for the Unified Medical Language System (UMLS) Concept Unique Identifiers (CUIs). These come from Andrew Beam's cui2vec R package.

Usage

dataset_cui2vec_definitions()

Format

A data frame with 3053795 rows and 3 variables:

cui

A Unified Medical Language System (UMLS) Concept Unique Identifier (CUI)

semantic_type

Semantic type of the CUI

definition

Definition of the CUI

Details

License

This data is made available under a MIT license. The data is copyrighted in 2019 by Benjamin Kompa, Andrew Beam, and Allen Schmaltz. The only change made to the original dataset is the renaming of columns.

Value

Returns the cui2vec UMLS definitions as a data frame.

Source

https://github.com/beamandrew/cui2vec

Cui2vec concept embeddings

Description

This dataset contains Unified Medical Langauge System (UMLS) concept embeddings from Andrew Beam's cui2vec R package. There are 500 embeddings included for each concept.

Usage

dataset_cui2vec_embeddings()

Format

A data frame with 109053 rows and 501 variables:

cui

A Unified Medical Language System (UMLS) Concept Unique Identifier (CUI)

emb_001

Concept embedding vector #1

emb_002

Concept embedding vector #2

...

and so on...

emb_500

Concept embedding vector #500

Details

This dataset is not viewable until it has been downloaded, which will occur the very first time you run clinspacy_init() after installing this package.

Citation

Beam, A.L., Kompa, B., Schmaltz, A., Fried, I., Griffin, W, Palmer, N.P., Shi, X., Cai, T., and Kohane, I.S.,, 2019. Clinical Concept Embeddings Learned from Massive Sources of Multimodal Medical Data. arXiv preprint arXiv:1804.01486.

License

This data is made available under a CC BY 4.0 license. The only change made to the original dataset is the renaming of columns.

Value

Returns the cui2vec UMLS embeddings as a data frame.

Source

https://figshare.com/s/00d69861786cd0156d81

Medical transcription samples.

Description

This dataset contains sample medical transcriptions for various medical specialties.

Usage

dataset_mtsamples()

Format

A data frame with 4999 rows and 6 variables:

note_id

A unique identifier for each note

description

A description or chief concern

medical_specialty

Medical specialty of the note

sample_name

mtsamples.com note name

transcription

Transcription of note text

keywords

Keywords

Details

Acknowledgements

This data was scraped from https://mtsamples.com by Tara Boyle.

License This data is made available under a CC0: Public Domain license.

Value

Returns the mtsamples dataset as a data frame.

Source

https://www.kaggle.com/tboyle10/medicaltranscriptions/data