Man pages for LBDiscover
Literature-Based Discovery Tools for Biomedical Research
| abc_model | Apply the ABC model for literature-based discovery with... |
| abc_model_opt | Optimize ABC model calculations for large matrices |
| abc_model_sig | Apply the ABC model with statistical significance testing |
| abc_timeslice | Apply time-sliced ABC model for validation |
| add_statistical_significance | Add statistical significance testing based on hypergeometric... |
| alternative_validation | Alternative validation for large matrices |
| anc_model | ANC model for literature-based discovery with biomedical term... |
| apply_bitola_flexible | Apply a flexible BITOLA-style discovery model without strict... |
| apply_correction | Apply correction to p-values |
| authenticate_umls | Authenticate with UMLS |
| bitola_model | Apply BITOLA-style discovery model |
| calc_bibliometrics | Calculate basic bibliometric statistics |
| calc_doc_sim | Calculate document similarity using TF-IDF and cosine... |
| calculate_score | Calculate ABC score based on specified method |
| clear_pubmed_cache | Clear PubMed cache |
| cluster_docs | Cluster documents using K-means |
| compare_terms | Compare term frequencies between two corpora |
| create_citation_net | Create a citation network from article data |
| create_comat | Create co-occurrence matrix without explicit entity type... |
| create_dummy_dictionary | Helper function to create dummy dictionaries |
| create_report | Generate a comprehensive discovery report |
| create_sparse_comat | Create a sparse co-occurrence matrix |
| create_tdm | Create a term-document matrix from preprocessed text |
| create_term_document_matrix | Create a term-document matrix from preprocessed text |
| detect_lang | Detect language of text |
| diversify_abc | Enforce diversity in ABC model results |
| diversify_b_terms | Enforce diversity by selecting top connections from each B... |
| diversify_c_paths | Enforce diversity for C term paths |
| dot-dict_cache_env | Environment to store dictionary cache data |
| dot-pubmed_cache_env | Environment to store PubMed cache data |
| enhance_abc_kb | Enhance ABC results with external knowledge |
| eval_evidence | Evaluate literature support for discovery results |
| export_chord | Export interactive HTML chord diagram for ABC connections |
| export_chord_diagram | Export interactive HTML chord diagram for ABC connections |
| export_network | Export ABC results to simple HTML network |
| extract_entities | Extract and classify entities from text with multi-domain... |
| extract_entities_workflow | Extract entities from text with improved efficiency using... |
| extract_mesh_from_text | Extract MeSH terms from text format instead of XML |
| extract_ner | Perform named entity recognition on text |
| extract_ngrams | Extract n-grams from text |
| extract_terms | Extract common terms from a corpus |
| extract_topics | Apply topic modeling to a corpus |
| fetch_and_parse_gene | Fetch and parse Gene data |
| fetch_and_parse_pmc | Fetch and parse PMC data |
| fetch_and_parse_protein | Fetch and parse Protein data |
| fetch_and_parse_pubmed | Fetch and parse PubMed data |
| filter_by_type | Filter a co-occurrence matrix by entity type |
| find_abc_all | Find all potential ABC connections |
| find_similar_docs | Find similar documents for a given document |
| find_term | Find primary term in co-occurrence matrix |
| gen_report | Generate comprehensive discovery report |
| get_dict_cache | Get dictionary cache environment |
| get_pmc_fulltext | Retrieve full text from PubMed Central |
| get_pubmed_cache | Get the pubmed cache environment |
| get_service_ticket | Get a service ticket from a TGT URL |
| get_term_vars | Extract term variations from text corpus |
| get_type_dist | Get entity type distribution from co-occurrence matrix |
| get_umls_semantic_types | Get UMLS semantic types for a given dictionary type |
| is_valid_biomedical_entity | Determine if a term is likely a specific biomedical entity... |
| list_to_df | Convert a list of articles to a data frame |
| load_dictionary | Load biomedical dictionaries with improved error handling |
| load_from_mesh | Load terms from MeSH using rentrez with improved error... |
| load_from_umls | Load terms from UMLS API |
| load_mesh_terms_from_pubmed | Load terms from MeSH using PubMed search |
| load_results | Load saved results from a file |
| lsi_model | LSI model with enhanced biomedical term filtering and NLP... |
| map_ontology | Map terms to biomedical ontologies |
| merge_entities | Combine and deduplicate entity datasets |
| merge_results | Merge multiple search results |
| min_results | Ensure minimum results for visualization |
| ncbi_search | Search NCBI databases for articles or data |
| null_coalesce | Null coalescing operator |
| parallel_analysis | Apply parallel processing for document analysis |
| parse_pubmed_xml | Parse PubMed XML data with optimized memory usage |
| perm_test_abc | Perform randomization test for ABC model |
| plot_heatmap | Create heatmap visualization from results |
| plot_network | Create network visualization from results |
| prep_articles | Prepare articles for report generation |
| preprocess_text | Preprocess article text |
| process_mesh_chunks | Process MeSH data in chunks to avoid memory issues |
| process_mesh_xml | Process MeSH XML data with improved error handling |
| pubmed_search | Search PubMed for articles with optimized performance |
| query_external_api | Query external biomedical APIs to validate entity types |
| query_mesh | Query for MeSH terms using E-utilities |
| query_umls | Query UMLS for term information |
| remove_ac_terms | Remove A and C terms that appear as B terms |
| retry_api_call | Retry an API call with exponential backoff |
| run_lbd | Perform comprehensive literature-based discovery without type... |
| safe_diversify | Diversify ABC results with error handling |
| sanitize_dictionary | Enhanced sanitize dictionary function |
| save_results | Save search results to a file |
| segment_sentences | Perform sentence segmentation on text |
| shadowtext | Helper function to draw text with a shadow/background |
| standard_validation | Standard validation method using hypergeometric tests |
| validate_abc | Apply statistical validation to ABC model results with... |
| validate_biomedical_entity | Validate biomedical entities using BioBERT or other ML models |
| validate_entity_comprehensive | Comprehensive entity validation using multiple techniques |
| validate_entity_with_nlp | Validate entity types using NLP-based entity recognition with... |
| validate_umls_key | Validate a UMLS API key |
| valid_entities | Filter entities to include only valid biomedical terms |
| vec_preprocess | Vectorized preprocessing of text |
| vis_abc_heatmap | Create a heatmap of ABC connections |
| vis_heatmap | Create an enhanced heatmap of ABC connections |
| vis_network | Create an enhanced network visualization of ABC connections |
| visualize_abc_network | Visualize ABC model results as a network |
