Update README.md

README.md

@@ -16,3 +16,26 @@ These 2 datasets contain no patient identifying information are openly available
 #### CSIRO: https://data.csiro.au/collection/csiro:17152
 
 
+
+Additionally, for the IR task, other feature representations of the documents have been created, each of these has exactly 374648 lines of corresponding data:
+
+doc_texts.csv
+- texts extracted from processed documents using several fields including eligbility min and max age, and eligbility criteria, structured as this example from NCT00000102:
+  "Inclusion Criteria: diagnosed with Congenital Adrenal Hyperplasia (CAH) normal ECG during baseline evaluation, Exclusion Criteria: history of liver disease, or elevated liver function tests history of cardiovascular disease"
+
+
+doc_categories.csv:
+- 1 x 15 vectors of somewhat arbitrarily chosen topic probabilities (softmax output) generated by zero-shot classification model, CTMatch.category_model(doc['condition']) lexically ordered as such:
+cancer,cardiac,endocrine,gastrointestinal,genetic,healthy,infection,neurological,other,pediatric,psychological,pulmonary,renal,reproductive
+
+doc_embeddings.csv:
+- 1 x 384 vectors of embeddings taken from last hidden state of CTMatch.embedding_model.encode(doc_text) using SentenceTransformers
+
+
+index2docid.csv
+- simple mapping of index to NCTID's for filtering/reference throughout IR program, corresponding to vector, texts representation order
+
+see repo for more information:
+https://github.com/semajyllek/ctmatch
+
+