import logging
from ClinicalTrials.runner import Runner
logging.basicConfig(level=logging.DEBUG)
# setup the runner
run = Runner(666, 'run-alternative')
run.catch_exceptions = False
#run.limit = 3
run.discard_cached = False
run.term = "pulmonary arterial hypertension"
# run.term = "juvenile rheumatoid arthritis"
run.analyze_eligibility = False
run.analyze_keypaths = set(['condition_browse', 'intervention_browse', 'intervention', 'keyword', 'primary_outcome', 'arm_group'])
# create a callback
def cb(success, trials):
if success:
# loop trials
for trial in trials:
doc = trial.doc or {}
print 'Trial "%s" [ %s ]' % (trial.title, trial.nct)
print ' keyw: %s' % '; '.join(doc.get('keyword') or [])
print ' cond: %s' % '; '.join(doc.get('condition_browse', {}).get('mesh_term', []))
print ' intr: %s' % '; '.join(doc.get('intervention_browse', {}).get('mesh_term', []))
print ' intn: %s' % "\n ----> ".join([p.get('intervention_name') or '' for p in doc.get('intervention', [])])
print ' prim: %s' % "\n ----> ".join([p.get('measure') or '' for p in doc.get('primary_outcome', [])])
# print ' armg: %s' % "\n ----> ".join([a.get('description') or '' for a in doc.get('arm_group', [])])
import logging
from ClinicalTrials.runner import Runner
logging.basicConfig(level=logging.DEBUG)
# setup the runner
run = Runner(666, 'run-alternative')
run.catch_exceptions = False
#run.limit = 3
run.discard_cached = False
run.term = "pulmonary arterial hypertension"
# run.term = "juvenile rheumatoid arthritis"
run.analyze_eligibility = False
run.analyze_keypaths = set([
'condition_browse', 'intervention_browse', 'intervention', 'keyword',
'primary_outcome', 'arm_group'
])
# create a callback
def cb(success, trials):
if success:
# loop trials
for trial in trials:
doc = trial.doc or {}
print 'Trial "%s" [ %s ]' % (trial.title, trial.nct)
print ' keyw: %s' % '; '.join(doc.get('keyword') or [])
print ' cond: %s' % '; '.join(
doc.get('condition_browse', {}).get('mesh_term', []))
print ' intr: %s' % '; '.join(
# setup NLP pipelines nlp_ctakes = cTAKES() nlp_metamap = MetaMap() nlp_nltkt = NLTKTags() #nlp_nltkt.cleanup = False # setup the runner run = Runner(666, 'run-test') run.catch_exceptions = False #run.limit = 3 run.discard_cached = False run.term = "juvenile rheumatoid arthritis" run.analyze_eligibility = False run.analyze_keypaths = set(['brief_summary']) # run.analyze_keypaths = set(['eligibility_inclusion', 'eligibility_exclusion', 'brief_summary', 'detailed_description']) run.add_pipeline(nlp_metamap) # run.add_pipeline(nlp_nltkt) # create a callback def cb(success, trials): if success: lookup = UMLSLookup() # loop trials for trial in trials: print 'Trial "%s" [ %s ]' % (trial.title, trial.nct) d = trial.analyzable_results()
