treatmentDosesRelation.py 10.2 KB
Newer Older
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265
import os
import re
import json
import csv
import requests
import ConceptExtractor 
import configparser
import mysql.connector

#Funcion que dado un json que contiene el id del documento, fecha y texto
#encuentra todas las metricas que aparecen en el
#Input: json
#Output: diccionario de metricas
def call_date_metric_ann_module(json_body):
    r = requests.post("http://138.4.130.153:8088/jkes/annotator/dateAnnotator", json=json_body)
    dictOutput = {}
    try:
        answer = r.json()["response"]
        for i in range(1,len(answer)):
              for key in answer[i].keys():
                      for j in range(0,len(answer[i][key])):
                          for k in range(0,len(answer[i][key][j])):

                                if(answer[i][key][j][k][5] == "METRIC"):
                                       if(answer[i][key][j][k][1] in dictOutput.keys()):
                                           lAux = dictOutput[answer[i][key][j][k][1]]
                                           lAux.append((answer[i][key][j][k][0],answer[i][key][j][k][2]))
                                           dictOutput[key] = lAux
                                       else:
                                           dictOutput[key] = [(answer[i][key][j][k][0],answer[i][key][j][k][2])]

    except:
        pass
    
    return dictOutput

#Funcion que lee las notas de un csv (cambiara cuando BERT nos devuelva el id del documento)
#Input: path al csv
#Output: diccionario de documentos
def read_documents(path):

	dictDocsOutput = {}

	if os.path.exists(path):   
		with open(path) as csv_file:
			csv_reader = csv.reader(csv_file, delimiter=',')
			for row in csv_reader:
				dictDocsOutput[row[0]] = row[5]

	return dictDocsOutput


#Funcion que lee el json de anotaciones de BERT
#Input: path al json de anotaciones
#Output: diccionario cuya clave es el id del documento y los valores son los ttos (chemotherapy_drug, radiotherapy_drug, medication) --> cambiar para recuperar las dosis cuando BERT las reconozca
def read_json_annotation(path):

	dictJsonOutput = {}

	if os.path.exists(path):          
		with open(path) as json_file:
			annotations = json.load(json_file)
			concepts = ConceptExtractor.extractionOfConcepts(annotations)
			
			for i in range(0,len(concepts)):
				if(len(concepts[i])==5):
					if(("CHEMOTHERAPY_DRUG" == concepts[i][1]) or ("RADIOTHERAPY_DRUG" == concepts[i][1]) or ("MEDICATION" == concepts[i][1])):
						if (concepts[i][4] in dictJsonOutput.keys()): 
							lAux  = dictJsonOutput[concepts[i][4]]
							lAux.append((concepts[i][0],concepts[i][2],concepts[i][3],concepts[i][4]))
							dictJsonOutput[concepts[i][4]] = lAux
						else:
							dictJsonOutput[concepts[i][4]] = [(concepts[i][0],concepts[i][2],concepts[i][3],concepts[i][4])]

	return dictJsonOutput

#Funcion que guarda los datos recopilados en las tablas dosage, treatment, note_dosage y note_treatment
def save_ttes_into_database(dictFinal):

	configuration = configparser.ConfigParser()
	configuration.read('config.ini')

	config = {'user':configuration['ARES']['DB_USER'],
	'password':configuration['ARES']['DB_PASSWORD'],
	'port':configuration['ARES']['DB_PORT'],
	'host':configuration['ARES']['DB_HOST'],
	'db':configuration['ARES']['DB_NAME'],
	'auth_plugin':configuration['ARES']['DB_AUTH_PLUGIN']
	}
	
	cnx = mysql.connector.connect(**config)
	#Creamos el cursor 
	cursor = cnx.cursor()

	queryLastId = "select max(treatment_id) from concept_extraction.treatment order by treatment_id asc;" #Obtenemos el ultimo id insertado en la tabla
	cursor.execute(queryLastId)
	lastIdTreatment = 0
	for row in cursor:
		if((row[0] is not None)  and (int(row[0])>=0)):
			lastIdTreatment = int(row[0]) + 1

	queryLastId = "select max(dosage_id) from concept_extraction.dosage order by dosage_id asc;" #Obtenemos el ultimo id insertado en la tabla
	cursor.execute(queryLastId)
	lastIdDosage = 0
	for row in cursor:
		if((row[0] is not None) and (int(row[0])>=0)):
			lastIdDosage = int(row[0]) + 1
	cursor.close()
	cnx.close()
	cnx = mysql.connector.connect(**config)
	cursor = cnx.cursor()

	for key in dictFinal:
		for i in range(0,len(dictFinal[key])):
			print(lastIdTreatment,lastIdDosage)
			query,query2,query3,query4="","","",""
			
			if((dictFinal[key][i][0]!="") and (dictFinal[key][i][3]=="")): #No hay dosis
				query = "insert ignore into concept_extraction.treatment (treatment_id,name) values ('"+str(lastIdTreatment)+"','"+str(dictFinal[key][i][0])+"');"
				query2 = "insert into concept_extraction.note_treatment (note_id,treatment_id,begin,end) values ('"+str(key)+"','"+str(lastIdTreatment)+"','"+str(dictFinal[key][i][1])+"','"+str(dictFinal[key][i][2])+"');"
			elif((dictFinal[key][i][0]!="") and (dictFinal[key][i][3]!="")): #Hay dosis
				query = "insert ignore into concept_extraction.treatment (name) values ('"+str(dictFinal[key][0])+"');"
				query2 = "insert into concept_extraction.note_treatment (note_id,treatment_id,begin,end) values ('"+str(key)+"','"+str(lastIdTreatment)+"','"+str(dictFinal[key][i][1])+"','"+str(dictFinal[key][i][2])+"');"
				query3 = "insert ignore into concept_extraction.dosage (dosage_id,description) values ('"+str(lastIdDosage)+"','"+dictFinal[key][i][3].encode("UTF8")+"');"
				query4 = "insert ignore into concept_extraction.note_dosage (note_id,dosage_id,begin,end) values ('"+str(key)+"','"+str(lastIdDosage)+"','"+str(dictFinal[key][i][4])+"','"+str(dictFinal[key][i][5])+"');"
			else: #Hay dosis pero no hay tto
				query3 = "insert ignore into concept_extraction.dosage (dosage_id,description) values ('"+str(lastIdDosage)+"','"+dictFinal[key][i][3].encode("UTF8")+"');"
				query4 = "insert ignore into concept_extraction.note_dosage (note_id,dosage_id,begin,end) values ('"+str(key)+"','"+str(lastIdDosage)+"','"+str(dictFinal[key][i][4])+"','"+str(dictFinal[key][i][5])+"');"
			
			if((query3!="") and (query4!="")):
				print(query3)
				cursor.execute(query3)
				cnx.commit()
				print(query4)
				cursor.execute(query4)
				cnx.commit()
				lastIdDosage += 1

			if((query!="") and (query2!="")):
				cursor.execute(query)
				cnx.commit()
				cursor.execute(query2)
				cnx.commit()
				lastIdTreatment += 1

	cursor.close()
	cnx.close()


#Funcion que relaciona los tratamientos y las metricas (cambiar cuando BERT las reconozca) que aparecen en un documento
#Input: documento, el diccionario de anotaciones BERT, el diccionario de metricas y el id del documento tratado
#Output: diccionario cuya clave es el id del documento y el valor es un listado de tuplas (tto,begin,end,dosis,begin,end) --> si no hay dosis relacionada, el campo dosis estara vacio y no habra begin ni end de la dosis
def relate_treatments(sentence,dictJsonOutput,dictOutput,key):
	
	lTreatments = []
	lDoses = []

	for i in range(0,len(dictJsonOutput[key])):
		if(dictJsonOutput[key][i][0] in sentence.lower()):
			indexes = [m.start() for m in re.finditer(dictJsonOutput[key][i][0].lower(), sentence.lower())] #Todas las ocurrencias
			if(dictJsonOutput[key][i][1] in indexes):
				lTreatments.append(dictJsonOutput[key][i])


	for i in range(0,len(dictOutput[key])):
		if(dictOutput[key][i][0] in sentence.lower()):
			index = sentence.lower().index(dictOutput[key][i][0].lower())
			if(dictOutput[key][i][1] == index):
				lDoses.append(dictOutput[key][i])

	dictFinal = {}

	for i in range(0,len(lTreatments)):
		j=0
		aux = ""
		enc = False
		while ((j<len(lDoses)) and (not enc)):
			if(abs(lTreatments[i][2]-lDoses[j][1])<=5): 
				aux = (lTreatments[i][0],lTreatments[i][1],lTreatments[i][2],lDoses[j][0],lDoses[j][1],(lDoses[j][1]+len(lDoses[j][0])))				
				enc = True
			j+=1

		if(not enc):
			aux = (lTreatments[i][0],lTreatments[i][1],lTreatments[i][2],"")

		if(lTreatments[i][3] in dictFinal): 
			lAux = dictFinal[lTreatments[i][3]]
			if (aux not in lAux):
				lAux.append(aux)
				dictFinal[lTreatments[i][3]] = lAux
		else:
			dictFinal[lTreatments[i][3]] = [aux]

				
	return dictFinal

#Path relativas a las anotaciones y a las notas (esto cambiara en cuanto BERT nos devuelva las dosis)
path = "/home/jarvos/Escritorio/Extractor/annotations.json"
pathDocuments = "/home/jarvos/Escritorio/Extractor/documentos_clarifyv2.csv"
dictJsonOutput = read_json_annotation(path)
dictDocsOutput = read_documents(pathDocuments)
#Fecha del documento, cambiara cuando BERT nos devuelva toda la informacion
fecha_doc="2021-02-09"

for key in dictJsonOutput.keys():

	json_body_example = {key: [fecha_doc, [dictDocsOutput[key]]]}
	dictOutput = call_date_metric_ann_module(json_body_example)
	dictFinal = {}

	#Si hay dosis y ttos en el mismo documento miramos si estan relacionadas
	if (key in dictOutput.keys()):
		dictFinal = relate_treatments(dictDocsOutput[key].decode("UTF8"),dictJsonOutput,dictOutput,key)

	#Si no hay nada relacionado, devolvemos los ttos encontrados y las dosis (en este caso, las dosis no estan relacionadas con los ttos)
	if ((not dictFinal) or (key not in dictOutput.keys())):

		v = dictJsonOutput[key]

		for i in range(0,len(v)):
				if(key in dictFinal.keys()):
					lAux = dictFinal[key]
					lAux.append((v[i][0],v[i][1],v[i][2],""))
					dictFinal[key] = lAux
				else:
					dictFinal[key] = [(v[i][0],v[i][1],v[i][2],"")]
	
	
	#Hay dosis pero no estn relacionadas con ningun tto
	if ((dictOutput) and (key in dictOutput.keys())): 
		v = dictOutput[key]
		
		for i in range(0,len(v)):
				print(v[i])
				if(key in dictFinal.keys()):
					lAux = dictFinal[key]
					lAux.append(("",0,0,v[i][0],v[i][1],v[i][1]+len(v[i][0])))
					dictFinal[key] = lAux
				else:
					dictFinal[key] = [("",0,0,v[i][0],v[i][1],v[i][1]+len(v[i][0]))]

	#print(dictFinal)
	save_ttes_into_database(dictFinal)

#Buscamos las dosis del resto de documentos en donde no hay ttos (hay que cambiarlo cuando este lo de BERT)
for key in dictDocsOutput.keys():
	if (key not in dictJsonOutput.keys()):
		json_body_example = {key: [fecha_doc, [dictDocsOutput[key]]]}
		dictOutput = call_date_metric_ann_module(json_body_example)
		dictFinal = {}

		if ((dictOutput) and (key in dictOutput.keys())): 
			v = dictOutput[key]
			
			for i in range(0,len(v)):
				if(key in dictFinal.keys()):
					lAux = dictFinal[key]
					lAux.append(("",0,0,v[i][0],v[i][1],v[i][1]+len(v[i][0])))
					dictFinal[key] = lAux
				else:
					dictFinal[key] = [("",0,0,v[i][0],v[i][1],v[i][1]+len(v[i][0]))]

			#print(dictFinal)
			save_ttes_into_database(dictFinal)