foreword
After the Neo4j database is constructed, it is time to realize the medical knowledge answering function. Because it is the first edition, the question answering here will not involve deep learning, and it is only a conditional query process at present. And this process includes dismantling and classifying the keywords of the question, then extracting words and types to query the graph database, and finally assembling the language according to the query result and question type to complete the answer. The following is the entire code flow for completing this process.
environment
In addition to the aforementioned environment, the environment required here also requires the ahocorasick library for extracting keywords from questions. The other is colorama, a library for beautifying text in the output panel.
coding
1. Q&A panel
from colorama import init,Fore,Style,Back
from classifier import Classifier
from parse import Parse
from answer import Answer
class ChatRobot:
def __init__(self):
init(autoreset=True)
print("====================================")
print(Back.BLUE+"欢迎进入智慧医疗问答面板！")
print("====================================")
def main(self, question):
print("")
default_answer = "您好，小北知识有限，暂时回答不上来，正在努力迭代中！"
final_classify = Classifier().classify(question)
parse_sql = Parse().main(final_classify)
final_answer = Answer().main(parse_sql)
if not final_answer:
return default_answer
return "\n\n".join(final_answer)
if __name__ == "__main__":
robot = ChatRobot()
while 1:
print(" ")
question = input("您问：")
if "关闭" in question:
print("")
print("小北说：", "好的，已经关闭了哦，欢迎您下次提问~")
break;
answer = robot.main(question)
print(Fore.LIGHTRED_EX+"小北答：", Fore.GREEN + answer)2. Problem classification
import ahocorasick
class Classifier:
def __init__(self):
# print("开始初始化：", time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()))
self.checks_wds = [i.strip() for i in open("dict/checks.txt", encoding="utf-8", mode="r") if i.strip()]
self.departments_wds = [i.strip() for i in open("dict/departments.txt", encoding="utf-8", mode="r") if i.strip()]
self.diseases_wds = [i.strip() for i in open("dict/diseases.txt", encoding="utf-8", mode="r") if i.strip()]
self.drugs_wds = [i.strip() for i in open("dict/drugs.txt", encoding="utf-8", mode="r") if i.strip()]
self.foods_wds = [i.strip() for i in open("dict/foods.txt", encoding="utf-8", mode="r") if i.strip()]
self.producers_wds = [i.strip() for i in open("dict/producers.txt", encoding="utf-8", mode="r") if i.strip()]
self.symptoms_wds = [i.strip() for i in open("dict/symptoms.txt", encoding="utf-8", mode="r") if i.strip()]
self.features_wds = set(self.checks_wds+self.departments_wds+self.diseases_wds+self.drugs_wds+self.foods_wds+self.producers_wds+self.symptoms_wds)
self.deny_words = [name.strip() for name in open("dict/deny.txt", encoding="utf-8", mode="r") if name.strip()]
# actree 从输入文本中提取出指定分词表中的词
self.actree = self.build_actree(list(self.features_wds))
# 给每个词创建类型词典（相当慢的操作）
self.wds_dict = self.build_words_dict()
# print("给每个词创建类型词典结束：", time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()))
# 问句疑问词
self.symptom_qwds = ['症状', '表征', '现象', '症候', '表现']
self.cause_qwds = ['原因', '成因', '为什么', '怎么会', '怎样才', '咋样才', '怎样会', '如何会', '为啥', '为何', '如何才会', '怎么才会', '会导致',
'会造成']
self.acompany_qwds = ['并发症', '并发', '一起发生', '一并发生', '一起出现', '一并出现', '一同发生', '一同出现', '伴随发生', '伴随', '共现']
self.food_qwds = ['饮食', '饮用', '吃', '食', '伙食', '膳食', '喝', '菜', '忌口', '补品', '保健品', '食谱', '菜谱', '食用', '食物', '补品']
self.drug_qwds = ['药', '药品', '用药', '胶囊', '口服液', '炎片']
self.prevent_qwds = ['预防', '防范', '抵制', '抵御', '防止', '躲避', '逃避', '避开', '免得', '逃开', '避开', '避掉', '躲开', '躲掉', '绕开',
'怎样才能不', '怎么才能不', '咋样才能不', '咋才能不', '如何才能不',
'怎样才不', '怎么才不', '咋样才不', '咋才不', '如何才不',
'怎样才可以不', '怎么才可以不', '咋样才可以不', '咋才可以不', '如何可以不',
'怎样才可不', '怎么才可不', '咋样才可不', '咋才可不', '如何可不']
self.lasttime_qwds = ['周期', '多久', '多长时间', '多少时间', '几天', '几年', '多少天', '多少小时', '几个小时', '多少年']
self.cureway_qwds = ['怎么治疗', '如何医治', '怎么医治', '怎么治', '怎么医', '如何治', '医治方式', '疗法', '咋治', '怎么办', '咋办', '咋治']
self.cureprob_qwds = ['多大概率能治好', '多大几率能治好', '治好希望大么', '几率', '几成', '比例', '可能性', '能治', '可治', '可以治', '可以医']
self.easyget_qwds = ['易感人群', '容易感染', '易发人群', '什么人', '哪些人', '感染', '染上', '得上']
self.check_qwds = ['检查', '检查项目', '查出', '检查', '测出', '试出']
self.belong_qwds = ['属于什么科', '属于', '什么科', '科室']
self.cure_qwds = ['治疗什么', '治啥', '治疗啥', '医治啥', '治愈啥', '主治啥', '主治什么', '有什么用', '有何用', '用处', '用途',
'有什么好处', '有什么益处', '有何益处', '用来', '用来做啥', '用来作甚', '需要', '要']
'''构造actree，加速过滤'''
def build_actree(self, wordlist):
actree = ahocorasick.Automaton()
for index, word in enumerate(wordlist):
actree.add_word(word, (index, word))
actree.make_automaton()
return actree
# 构建特征词属性
def build_words_dict(self):
words_dict = {}
check_words = set(self.checks_wds)
department_words = set(self.departments_wds)
disease_words = set(self.diseases_wds)
drug_words = set(self.drugs_wds)
food_words = set(self.foods_wds)
producer_words = set(self.producers_wds)
symptom_words = set(self.symptoms_wds)
for word in self.features_wds:
words_dict[word] = []
if word in check_words:
words_dict[word].append("check")
if word in department_words:
words_dict[word].append("department")
if word in disease_words:
words_dict[word].append("disease")
if word in drug_words:
words_dict[word].append("drug")
if word in food_words:
words_dict[word].append("food")
if word in producer_words:
words_dict[word].append("producer")
if word in symptom_words:
words_dict[word].append("symptom")
return words_dict
# 根据输入返回问题类型
def classify(self, sent):
# 最终输入给解析器的字典
data = {}
region_words = []
lists = self.actree.iter(sent)
for ii in lists:
cur_word = ii[1][1]
region_words.append(cur_word)
# {'职业黑变病': ['diseases'], '倒睫': ['diseases', 'symptom']}
final_dict = {i_name: self.wds_dict.get(i_name) for i_name in region_words}
data['args'] = final_dict
question_type = "other"
questions_type = []
# ['diseases', 'diseases', 'symptom']
type = []
for i_type in final_dict.values():
type += i_type
# 判断type中是否有指定类型, 提出的问题是否包含指定的修饰词，给问题定类型
# 1. 如提问词是否出现状态词语，那就是问某种疾病会出现什么症状
if self.check_word_exist(self.symptom_qwds, sent) and ('disease' in type):
question_type = "disease_symptom"
questions_type.append(question_type)
# 根据症状问疾病
if self.check_word_exist(self.symptom_qwds, sent) and ('symptom' in type):
question_type = "symptom_disease"
questions_type.append(question_type)
# 原因
if self.check_word_exist(self.cause_qwds, sent) and ('disease' in type):
question_type = 'disease_cause'
questions_type.append(question_type)
# 并发症
if self.check_word_exist(self.acompany_qwds, sent) and ('disease' in type):
question_type = 'disease_acompany'
questions_type.append(question_type)
# 推荐食品
if self.check_word_exist(self.food_qwds, sent) and 'disease' in type:
deny_status = self.check_word_exist(self.deny_words, sent)
if deny_status:
question_type = 'disease_not_food'
else:
question_type = 'disease_do_food'
questions_type.append(question_type)
# 已知食物找疾病
if self.check_word_exist(self.food_qwds + self.cure_qwds, sent) and 'food' in type:
deny_status = self.check_word_exist(self.deny_words, sent)
if deny_status:
question_type = 'food_not_disease'
else:
question_type = 'food_do_disease'
questions_type.append(question_type)
# 推荐药品
if self.check_word_exist(self.drug_qwds, sent) and 'disease' in type:
question_type = 'disease_drug'
questions_type.append(question_type)
# 药品治啥病
if self.check_word_exist(self.cure_qwds, sent) and 'drug' in type:
question_type = 'drug_disease'
questions_type.append(question_type)
# 疾病接受检查项目
if self.check_word_exist(self.check_qwds, sent) and 'disease' in type:
question_type = 'disease_check'
questions_type.append(question_type)
# 已知检查项目查相应疾病
if self.check_word_exist(self.check_qwds + self.cure_qwds, sent) and 'check' in type:
question_type = 'check_disease'
questions_type.append(question_type)
# 症状防御
if self.check_word_exist(self.prevent_qwds, sent) and 'disease' in type:
question_type = 'disease_prevent'
questions_type.append(question_type)
# 疾病医疗周期
if self.check_word_exist(self.lasttime_qwds, sent) and 'disease' in type:
question_type = 'disease_lasttime'
questions_type.append(question_type)
# 疾病治疗方式
if self.check_word_exist(self.cureway_qwds, sent) and 'disease' in type:
question_type = 'disease_cureway'
questions_type.append(question_type)
# 疾病治愈可能性
if self.check_word_exist(self.cureprob_qwds, sent) and 'disease' in type:
question_type = 'disease_cureprob'
questions_type.append(question_type)
# 疾病易感染人群
if self.check_word_exist(self.easyget_qwds, sent) and 'disease' in type:
question_type = 'disease_easyget'
questions_type.append(question_type)
# 若没有查到相关的外部查询信息，那么则将该疾病的描述信息返回
if questions_type == [] and 'disease' in type:
questions_type = ['disease_desc']
# 若没有查到相关的外部查询信息，那么则将该疾病的描述信息返回
if questions_type == [] and 'symptom' in type:
questions_type = ['symptom_disease']
# 将多个分类结果进行合并处理，组装成一个字典
data['question_types'] = questions_type
return data
def check_word_exist(self, word_list, words):
for item in word_list:
if item in words:
return True
return False
3. Type resolution (query assembly)
class Parse:
def main(self, classify):
entity = classify['args']
questions_type = classify['question_types']
entity_dict = self.entity_transform(entity)
sqls = []
for question in questions_type:
sql_dict = {}
sql_dict["qustion_type"] = question
sql_dict["sql"] = []
sql = []
if question == 'disease_symptom':
sql = self.sql_transfer(question, entity_dict.get('disease'))
elif question == 'symptom_disease':
sql = self.sql_transfer(question, entity_dict.get('symptom'))
elif question == 'disease_cause':
sql = self.sql_transfer(question, entity_dict.get('disease'))
elif question == 'disease_acompany':
sql = self.sql_transfer(question, entity_dict.get('disease'))
elif question == 'disease_not_food':
sql = self.sql_transfer(question, entity_dict.get('disease'))
elif question == 'disease_do_food':
sql = self.sql_transfer(question, entity_dict.get('disease'))
elif question == 'food_not_disease':
sql = self.sql_transfer(question, entity_dict.get('food'))
elif question == 'food_do_disease':
sql = self.sql_transfer(question, entity_dict.get('food'))
elif question == 'disease_drug':
sql = self.sql_transfer(question, entity_dict.get('disease'))
elif question == 'drug_disease':
sql = self.sql_transfer(question, entity_dict.get('drug'))
elif question == 'disease_check':
sql = self.sql_transfer(question, entity_dict.get('disease'))
elif question == 'check_disease':
sql = self.sql_transfer(question, entity_dict.get('check'))
elif question == 'disease_prevent':
sql = self.sql_transfer(question, entity_dict.get('disease'))
elif question == 'disease_lasttime':
sql = self.sql_transfer(question, entity_dict.get('disease'))
elif question == 'disease_cureway':
sql = self.sql_transfer(question, entity_dict.get('disease'))
elif question == 'disease_cureprob':
sql = self.sql_transfer(question, entity_dict.get('disease'))
elif question == 'disease_easyget':
sql = self.sql_transfer(question, entity_dict.get('disease'))
elif question == 'disease_desc':
sql = self.sql_transfer(question, entity_dict.get('disease'))
if sql:
sql_dict['sql'] = sql
sqls.append(sql_dict)
return sqls
def sql_transfer(self, question_type, entities):
# 查询语句
sql = []
# 查询疾病的原因
if question_type == 'disease_cause':
sql = ["MATCH (m:Diseases) where m.name = '{0}' return m.name, m.cause".format(i) for i in entities]
# 查询疾病的防御措施
elif question_type == 'disease_prevent':
sql = ["MATCH (m:Diseases) where m.name = '{0}' return m.name, m.prevent".format(i) for i in entities]
# 查询疾病的持续时间
elif question_type == 'disease_lasttime':
sql = ["MATCH (m:Diseases) where m.name = '{0}' return m.name, m.cure_lasttime".format(i) for i in entities]
# 查询疾病的治愈概率
elif question_type == 'disease_cureprob':
sql = ["MATCH (m:Diseases) where m.name = '{0}' return m.name, m.cured_prob".format(i) for i in entities]
# 查询疾病的治疗方式
elif question_type == 'disease_cureway':
sql = ["MATCH (m:Diseases) where m.name = '{0}' return m.name, m.cure_way".format(i) for i in entities]
# 查询疾病的易发人群
elif question_type == 'disease_easyget':
sql = ["MATCH (m:Diseases) where m.name = '{0}' return m.name, m.easy_get".format(i) for i in entities]
# 查询疾病的相关介绍
elif question_type == 'disease_desc':
sql = ["MATCH (m:Diseases) where m.name = '{0}' return m.name, m.desc".format(i) for i in entities]
# 查询疾病有哪些症状
elif question_type == 'disease_symptom':
sql = [
"MATCH (m:Diseases)-[r:has_symptoms]->(n:Symptoms) where m.name = '{0}' return m.name, r.name, n.name".format(
i) for i in entities]
# 查询症状会导致哪些疾病
elif question_type == 'symptom_disease':
sql = [
"MATCH (m:Diseases)-[r:has_symptoms]->(n:Symptoms) where n.name = '{0}' return m.name, r.name, n.name".format(
i) for i in entities]
# 查询疾病的并发症
elif question_type == 'disease_acompany':
sql1 = [
"MATCH (m:Diseases)-[r:acompany_with]->(n:Symptoms) where m.name = '{0}' return m.name, r.name, n.name".format(
i) for i in entities]
sql2 = [
"MATCH (m:Diseases)-[r:acompany_with]->(n:Symptoms) where n.name = '{0}' return m.name, r.name, n.name".format(
i) for i in entities]
sql = sql1 + sql2
# 查询疾病的忌口
elif question_type == 'disease_not_food':
sql = ["MATCH (m:Diseases)-[r:not_eat]->(n:Foods) where m.name = '{0}' return m.name, r.name, n.name".format(i)
for i in entities]
# 查询疾病建议吃的东西
elif question_type == 'disease_do_food':
sql1 = [
"MATCH (m:Diseases)-[r:do_eat]->(n:Foods) where m.name = '{0}' return m.name, r.name, n.name".format(i)
for i in entities]
sql2 = [
"MATCH (m:Diseases)-[r:recomment_eat]->(n:Foods) where m.name = '{0}' return m.name, r.name, n.name".format(
i) for i in entities]
sql = sql1 + sql2
# 已知忌口查疾病
elif question_type == 'food_not_disease':
sql = ["MATCH (m:Diseases)-[r:not_eat]->(n:Foods) where n.name = '{0}' return m.name, r.name, n.name".format(i)
for i in entities]
# 已知推荐查疾病
elif question_type == 'food_do_disease':
sql1 = [
"MATCH (m:Diseases)-[r:do_eat]->(n:Foods) where n.name = '{0}' return m.name, r.name, n.name".format(i)
for i in entities]
sql2 = [
"MATCH (m:Diseases)-[r:recomment_eat]->(n:Foods) where n.name = '{0}' return m.name, r.name, n.name".format(
i) for i in entities]
sql = sql1 + sql2
# 查询疾病常用药品－药品别名记得扩充
elif question_type == 'disease_drug':
sql1 = [
"MATCH (m:Diseases)-[r:common_drug]->(n:Drugs) where m.name = '{0}' return m.name, r.name, n.name".format(
i) for i in entities]
sql2 = [
"MATCH (m:Diseases)-[r:recommand_drug]->(n:Drugs) where m.name = '{0}' return m.name, r.name, n.name".format(
i) for i in entities]
sql = sql1 + sql2
# 已知药品查询能够治疗的疾病
elif question_type == 'drug_disease':
sql1 = [
"MATCH (m:Diseases)-[r:common_drug]->(n:Drugs) where n.name = '{0}' return m.name, r.name, n.name".format(
i) for i in entities]
sql2 = [
"MATCH (m:Diseases)-[r:recommand_drug]->(n:Drugs) where n.name = '{0}' return m.name, r.name, n.name".format(
i) for i in entities]
sql = sql1 + sql2
# 查询疾病应该进行的检查
elif question_type == 'disease_check':
sql = [
"MATCH (m:Diseases)-[r:need_check]->(n:Checks) where m.name = '{0}' return m.name, r.name, n.name".format(
i) for i in entities]
# 已知检查查询疾病
elif question_type == 'check_disease':
sql = [
"MATCH (m:Diseases)-[r:need_check]->(n:Checks) where n.name = '{0}' return m.name, r.name, n.name".format(
i) for i in entities]
return sql
def entity_transform(self, entity):
entity_dict = {}
for args, types in entity.items():
for type in types:
if type in entity_dict:
entity_dict[type] = [args]
else:
entity_dict[type] = []
entity_dict[type].append(args)
return entity_dict4. Data query (answer assembly)
from py2neo import Graph, Node
class Answer:
def __init__(self):
self.neo4j = Graph('bolt://localhost:7687', auth=('neo4j', 'beiqiaosu123456'))
self.num_limit = 20
def main(self, question_parse):
answers_final = []
for item in question_parse:
question_type = item['qustion_type']
sqls = item['sql']
answer = []
for sql in sqls:
data = self.neo4j.run(sql)
answer+=data.data()
final_answer = self.answer_prettify(question_type, answer)
if final_answer:
answers_final.append(final_answer)
return answers_final
'''根据对应的qustion_type，调用相应的回复模板'''
def answer_prettify(self, question_type, answers):
final_answer = []
if not answers:
return ''
if question_type == 'disease_symptom':
desc = [i['n.name'] for i in answers]
subject = answers[0]['m.name']
final_answer = '{0}的症状包括：{1}'.format(subject, '；'.join(list(set(desc))[:self.num_limit]))
elif question_type == 'symptom_disease':
desc = [i['m.name'] for i in answers]
subject = answers[0]['n.name']
final_answer = '症状{0}可能染上的疾病有：{1}'.format(subject, '；'.join(list(set(desc))[:self.num_limit]))
elif question_type == 'disease_cause':
desc = [i['m.cause'] for i in answers]
subject = answers[0]['m.name']
final_answer = '{0}可能的成因有：{1}'.format(subject, '；'.join(list(set(desc))[:self.num_limit]))
elif question_type == 'disease_prevent':
desc = [i['m.prevent'] for i in answers]
subject = answers[0]['m.name']
final_answer = '{0}的预防措施包括：{1}'.format(subject, '；'.join(list(set(desc))[:self.num_limit]))
elif question_type == 'disease_lasttime':
desc = [i['m.cure_lasttime'] for i in answers]
subject = answers[0]['m.name']
final_answer = '{0}治疗可能持续的周期为：{1}'.format(subject, '；'.join(list(set(desc))[:self.num_limit]))
elif question_type == 'disease_cureway':
desc = [';'.join(i['m.cure_way']) for i in answers]
subject = answers[0]['m.name']
final_answer = '{0}可以尝试如下治疗：{1}'.format(subject, '；'.join(list(set(desc))[:self.num_limit]))
elif question_type == 'disease_cureprob':
desc = [i['m.cured_prob'] for i in answers]
subject = answers[0]['m.name']
final_answer = '{0}治愈的概率为（仅供参考）：{1}'.format(subject, '；'.join(list(set(desc))[:self.num_limit]))
elif question_type == 'disease_easyget':
desc = [i['m.easy_get'] for i in answers]
subject = answers[0]['m.name']
final_answer = '{0}的易感人群包括：{1}'.format(subject, '；'.join(list(set(desc))[:self.num_limit]))
elif question_type == 'disease_desc':
desc = [i['m.desc'] for i in answers]
subject = answers[0]['m.name']
final_answer = '{0},熟悉一下：{1}'.format(subject, '；'.join(list(set(desc))[:self.num_limit]))
elif question_type == 'disease_acompany':
desc1 = [i['n.name'] for i in answers]
desc2 = [i['m.name'] for i in answers]
subject = answers[0]['m.name']
desc = [i for i in desc1 + desc2 if i != subject]
final_answer = '{0}的症状包括：{1}'.format(subject, '；'.join(list(set(desc))[:self.num_limit]))
elif question_type == 'disease_not_food':
desc = [i['n.name'] for i in answers]
subject = answers[0]['m.name']
final_answer = '{0}忌食的食物包括有：{1}'.format(subject, '；'.join(list(set(desc))[:self.num_limit]))
elif question_type == 'disease_do_food':
do_desc = [i['n.name'] for i in answers if i['r.name'] == '可以吃']
recommand_desc = [i['n.name'] for i in answers if i['r.name'] == '推荐吃']
subject = answers[0]['m.name']
final_answer = '{0}宜食的食物包括有：{1}\n推荐食谱包括有：{2}'.format(subject, ';'.join(list(set(do_desc))[:self.num_limit]),
';'.join(list(set(recommand_desc))[:self.num_limit]))
elif question_type == 'food_not_disease':
desc = [i['m.name'] for i in answers]
subject = answers[0]['n.name']
final_answer = '患有{0}的人最好不要吃{1}'.format('；'.join(list(set(desc))[:self.num_limit]), subject)
elif question_type == 'food_do_disease':
desc = [i['m.name'] for i in answers]
subject = answers[0]['n.name']
final_answer = '患有{0}的人建议多试试{1}'.format('；'.join(list(set(desc))[:self.num_limit]), subject)
elif question_type == 'disease_drug':
desc = [i['n.name'] for i in answers]
subject = answers[0]['m.name']
final_answer = '{0}通常的使用的药品包括：{1}'.format(subject, '；'.join(list(set(desc))[:self.num_limit]))
elif question_type == 'drug_disease':
desc = [i['m.name'] for i in answers]
subject = answers[0]['n.name']
final_answer = '{0}主治的疾病有{1},可以试试'.format(subject, '；'.join(list(set(desc))[:self.num_limit]))
elif question_type == 'disease_check':
desc = [i['n.name'] for i in answers]
subject = answers[0]['m.name']
final_answer = '{0}通常可以通过以下方式检查出来：{1}'.format(subject, '；'.join(list(set(desc))[:self.num_limit]))
elif question_type == 'check_disease':
desc = [i['m.name'] for i in answers]
subject = answers[0]['n.name']
final_answer = '通常可以通过{0}检查出来的疾病有{1}'.format(subject, '；'.join(list(set(desc))[:self.num_limit]))
return final_answer
write at the end
The above is the entire code of this medical knowledge question answering robot. It can also be seen from the above question and answer that the answer is still very blunt. Because this is just a programmed mind map, there is still a lot of room for modification and improvement. This requires deep learning to modify the classification and analysis part later.