import sys
import os
import time
import operator
import cx_Oracle
import numpy as np
import pandas as pd
import tensorflow as tf
conn=cx_Oracle.connect('doctor/admin@localhost:1521/tszr')
cursor = conn.cursor()
def printHistory(userid):
sql = "select username,sex,age,province,area,bumen,ke,result,chufang,jianyi,yiyuaan,yisheng,jianchaxiang,zhenduanriqi from zhenduanjilutable where userid='%d'" % userid
cursor.execute(sql)
rows = cursor.fetchall()
zhenduanjilu = []
for row in rows:
temp = []
temp.append(row[0])
temp.append(row[1])
temp.append(row[2])
temp.append(row[3])
temp.append(row[4])
temp.append(row[5])
temp.append(row[6])
temp.append(row[7])
temp.append(row[8])
temp.append(row[9])
temp.append(row[10])
temp.append(row[11])
temp.append(row[12])
temp.append(row[13])
zhenduanjilu.append(temp)
print("===================打印诊断历史记录=====================")
for i in range(len(zhenduanjilu)):
print("-------------->>第："+str(i+1)+"次诊断<<-------------------")
print(" 姓名："+zhenduanjilu[i][0])
print(" 性别："+zhenduanjilu[i][1])
print(" 年龄："+str(zhenduanjilu[i][2]))
print(" 省份："+zhenduanjilu[i][3])
print(" 市区："+zhenduanjilu[i][4])
print(" 门诊部门："+zhenduanjilu[i][5])
print(" 门诊科目："+zhenduanjilu[i][6])
print(" 诊断结果："+zhenduanjilu[i][7])
print(" 医疗处方："+zhenduanjilu[i][8])
print(" 养生建议："+zhenduanjilu[i][9])
print(" 推荐医院："+zhenduanjilu[i][10])
print(" 推荐医生："+zhenduanjilu[i][11])
print(" 建议检查项："+zhenduanjilu[i][12])
print(" 诊断日期："+str(zhenduanjilu[i][13]))
# printHistory(6)
<%--
Document : ALfuzhengetAnswer
Created on : 2018-10-10, 11:00:12
Author : acer
--%>
<%@page import="java.util.Iterator"%>
<%@page import="java.util.ArrayList"%>
<%@page import="java.util.List"%>
<%@page import="java.io.InputStreamReader"%>
<%@page import="java.io.BufferedReader"%>
<%@page contentType="text/html" pageEncoding="UTF-8"%>
<!DOCTYPE html>
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<title>智能复诊页</title>
</head>
<% request.setCharacterEncoding("UTF-8");%>
<body>
<center><h2>智能复诊结果单</h2></center>
<hr>
<%
String userid = request.getParameter("userid");
String username = request.getParameter("username");
String province = request.getParameter("province");
String administ = request.getParameter("administ");
String surgest = request.getParameter("surgest");
String subject = request.getParameter("subject");
String one = request.getParameter("one");
String two = request.getParameter("two");
String three = request.getParameter("three");
String force = request.getParameter("force");
String five = request.getParameter("five");
String q1 = request.getParameter("q1");
q1 = q1 + one;
String q2 = request.getParameter("q2");
q2 = q2 + two;
String q3 = request.getParameter("q3");
q3 = q3 + three;
String q4 = request.getParameter("q4");
q4 = q4 + force;
String q5 = request.getParameter("q5");
q5 = q5 + five;
String qone = "";
if (one.equals("正常")) {
qone = "1";
} else if (one.equals("轻度")) {
qone = "2";
} else if (one.equals("偏重")) {
qone = "3";
} else {
qone = "4";
}
String qtow = "";
if (two.equals("正常")) {
qtow = "1";
} else if (two.equals("轻度")) {
qtow = "2";
} else if (two.equals("偏重")) {
qtow = "3";
} else {
qtow = "4";
}
String qthree = "";
if (three.equals("正常")) {
qthree = "1";
} else if (three.equals("轻度")) {
qthree = "2";
} else if (three.equals("偏重")) {
qthree = "3";
} else {
qthree = "4";
}
String qforce = "";
if (force.equals("正常")) {
qforce = "1";
} else if (force.equals("轻度")) {
qforce = "2";
} else if (force.equals("偏重")) {
qforce = "3";
} else {
qforce = "4";
}
String qfive = "";
if (five.equals("正常")) {
qfive = "1";
} else if (five.equals("轻度")) {
qfive = "2";
} else if (five.equals("偏重")) {
qfive = "3";
} else {
qfive = "4";
}
%>
<table width="874" cellspacing="0" cellpadding="0" border="1">
<tr><td><h3>就诊编号：<%=userid%></h3></td></tr>
<tr><td><h3>用户账号：<%=username%></h3></td></tr>
<tr><td><h3>门诊部门：<%=surgest%></h3></td></tr>
<tr><td><h3>病理科室：<%=subject%></h3></td></tr>
<tr><td><h3>问诊一：<%=q1%></h3></td></tr>
<tr><td><h3>问诊二：<%=q2%></h3></td></tr>
<tr><td><h3>问诊三：<%=q3%></h3></td></tr>
<tr><td><h3>问诊四：<%=q4%></h3></td></tr>
<tr><td><h3>问诊五：<%=q5%></h3></td></tr>
<tr><td>
<%
String[] userInfo = new String[]{"python", "F:\HostitalProject\src\java\pyFile\chuzhen.py", qone, qtow, qthree, qforce, qfive, userid, username, surgest, subject, province, administ};
Process pr = Runtime.getRuntime().exec(userInfo);
BufferedReader in = new BufferedReader(new InputStreamReader(pr.getInputStream()));
List<String> allList = new ArrayList<>();
String line;
while ((line = in.readLine()) != null) {
allList.add(line);
}
Iterator<String> iter = allList.iterator();
int length = allList.size();
String[] str_back = new String[length];
for (int i = 0; i < str_back.length; i++) {
str_back[i] = iter.next();
}
%>
<h3>诊断结果：<%=str_back[0]%> </h3>
<h3><%=str_back[1]%></h3>
<h3><%=str_back[2]%></h3>
<h3><%=str_back[3]%></h3>
<h3><%=str_back[4]%></h3>
<h3><%=str_back[5]%></h3>
<h3><%=str_back[6]%></h3>
<h3><%=str_back[7]%></h3>
<h3><%=str_back[8]%></h3>
<h3><%=str_back[9]%></h3>
<h3><%=str_back[10]%></h3>
<h3><%=str_back[11]%></h3>
<h3><%=str_back[12]%></h3>
<h3><%=str_back[13]%></h3>
</td></tr>
</table>
<h2><a href="log.html">返回登录页</a></h2>
</body>
</html>
#诊断逻辑代码
import sys
import os
import time
import operator
import cx_Oracle
import numpy as np
import pandas as pd
import tensorflow as tf
conn=cx_Oracle.connect('doctor/admin@localhost:1521/tszr')
cursor = conn.cursor()
# one-hot编码
def onehot(labels):
n_sample = len(labels)
n_class = max(labels) + 1
onehot_labels = np.zeros((n_sample, n_class))
onehot_labels[np.arange(n_sample), labels] = 1
return onehot_labels
# 获取数据集
def getdata(surgery ,surgeryChest):
sql = "select feature1,feature2,feature3,feature4,feature5,trainLable from menzhen where surgery='%s' and surgeryChest='%s'" %
(surgery, surgeryChest)
cursor.execute(sql)
rows = cursor.fetchall()
dataset = []
lables = []
for row in rows:
temp = []
temp.append(row[0])
temp.append(row[1])
temp.append(row[2])
temp.append(row[3])
temp.append(row[4])
dataset.append(temp)
if (row[5] == 3):
lables.append(0)
elif (row[5] == 6):
lables.append(1)
else:
lables.append(2)
dataset = np.array(dataset)
lables = np.array(lables)
dataset = dataset.astype(np.float32)
labless = onehot(lables)
return dataset, labless
def getAnswer(a1, a2, a3, a4, a5):
answers = []
answers.append(int(a1))
answers.append(int(a2))
answers.append(int(a3))
answers.append(int(a4))
answers.append(int(a5))
str_answers = []
if (int(a1) == 1):
str_answers.append("正常")
elif (int(a1) == 2):
str_answers.append("轻度")
elif (int(a1) == 3):
str_answers.append("偏重")
else:
str_answers.append("严重")
if (int(a2) == 1):
str_answers.append("正常")
elif (int(a2) == 2):
str_answers.append("轻度")
elif (int(a2) == 3):
str_answers.append("偏重")
else:
str_answers.append("严重")
if (int(a3) == 1):
str_answers.append("正常")
elif (int(a3) == 2):
str_answers.append("轻度")
elif (int(a3) == 3):
str_answers.append("偏重")
else:
str_answers.append("严重")
if (int(a4) == 1):
str_answers.append("正常")
elif (int(a4) == 2):
str_answers.append("轻度")
elif (int(a4) == 3):
str_answers.append("偏重")
else:
str_answers.append("严重")
if (int(a5) == 1):
str_answers.append("正常")
elif (int(a5) == 2):
str_answers.append("轻度")
elif (int(a5) == 3):
str_answers.append("偏重")
else:
str_answers.append("严重")
return answers, str_answers
def getSugessiones(sujects, resultName):
sql = "select prescription_1,prescription_2,prescription_3,prescription_4,prescription_5,prescription_6,prescription_7,prescription_8,prescription_9,prescription_10,prescription_11,prescription_12,prescription_13,prescription_14,prescription_15 from prescription where SURGERYCHEST='%s' and illName='%s'" % (
sujects, resultName)
cursor.execute(sql)
rows = cursor.fetchall()
prescriptionData = []
for row in rows:
one = []
one.append(row[0])
one.append(row[1])
one.append(row[2])
one.append(row[3])
one.append(row[4])
one.append(row[5])
one.append(row[6])
one.append(row[7])
one.append(row[8])
one.append(row[9])
one.append(row[10])
one.append(row[11])
one.append(row[12])
one.append(row[13])
one.append(row[14])
prescriptionData.append(one)
prescriptionDataFrame = pd.DataFrame(prescriptionData)
prescriptionDataSum = prescriptionDataFrame.sum(axis=0)
prescriptionDataSumSorted = sorted(enumerate(prescriptionDataSum), key=lambda x: x[1], reverse=True)
prescriptionDataSumSortedThirst = prescriptionDataSumSorted[:3]
prescriptionIndex = []
for i in range(len(prescriptionDataSumSortedThirst)):
prescriptionIndex.append(prescriptionDataSumSortedThirst[i][0])
sql = "select prescriptionInfo,health from prescriptionInfo where FAMILY='%s' and ill_name='%s'" % (
sujects, resultName)
cursor.execute(sql)
rows = cursor.fetchall()
prescriptionInfoData = []
healthData = []
for row in rows:
prescriptionInfoData.append(row[0])
healthData.append(row[1])
prescriptionInfoResult = []
for i in range(len(prescriptionIndex)):
prescriptionInfoResult.append(prescriptionInfoData[prescriptionIndex[i]])
healthResult = []
for i in range(len(prescriptionIndex)):
healthResult.append(healthData[prescriptionIndex[i]])
return prescriptionInfoResult, healthResult
def getSeeProject(subject):
sql = "select CHACKPRO from chackProject where FAMILY='%s'" % (subject)
cursor.execute(sql)
rows = cursor.fetchall()
seeproject = []
for row in rows:
seeproject.append(rows[0])
return seeproject[0][0]
def getDoctors(sujects):
sql = "select addraction,name,summary from doctors where family='%s'" % (sujects)
cursor.execute(sql)
rows = cursor.fetchall()
doctorInfo = []
for row in rows:
doctorInfo.append(row[0])
doctorInfo.append(row[1])
doctorInfo.append(row[2])
print("主治专家姓名：" + doctorInfo[1])
print("主治专家简介：" + doctorInfo[2])
print("主治专家所在医院：" + doctorInfo[0])
return doctorInfo
def getPAH(province, administrative):
sql = "select hostitalname from hostitalAdrrest where province='%s' and administrative='%s'" % (
province, administrative)
cursor.execute(sql)
rows = cursor.fetchall()
hostitalName = []
for row in rows:
hostitalName.append(row[0])
yiyuaan = ""
for i in range(len(hostitalName)):
print(hostitalName[i])
yiyuaan += hostitalName[i]
return yiyuaan
def addUser_SeeIll(userid, username, sex, age, province, area, bumen, ke, result, chufang, jianyi, yiyuaan, yisheng,
jianchaxiang):
sql = "insert into zhenduanjilutable (userid,username,sex,age,province,area,bumen,ke,result,chufang,jianyi,yiyuaan,yisheng,jianchaxiang) values (%d,'%s','%s','%s','%s','%s','%s','%s','%s','%s','%s','%s','%s','%s')" % (
userid, username, sex, age, province, area, bumen, ke, result, chufang, jianyi, yiyuaan, yisheng, jianchaxiang)
cursor.execute(sql)
conn.commit()
if (cursor.rowcount == 1):
print("新看病记录添加成功")
else:
print("新看病记录添加失败")
def zhenduan_n(a1, a2, a3, a4, a5, userid, username, surgery, surgeryChest, province, administ):
answers, str_answers = getAnswer(a1, a2, a3, a4, a5)
useranswer = [answers] * 3
dataset, labless = getdata(surgery, surgeryChest)
x_data = tf.placeholder("float32", [None, 5])
y_data = tf.placeholder("float32", [None, 3])
weight = tf.Variable(tf.ones([5, 3]))
bias = tf.Variable(tf.ones([3]))
# 使用softmax激活函数
y_model = tf.nn.softmax(tf.matmul(x_data, weight) + bias)
# y_model = tf.nn.relu(tf.matmul(x_data, weight) + bias)
# loss = tf.reduce_sum(tf.pow((y_model - y_data), 2))
# 使用交叉熵作为损失函数
loss = -tf.reduce_sum(y_data * tf.log(y_model))
# train_step = tf.train.GradientDescentOptimizer(1e-4).minimize(loss)
# 使用AdamOptimizer优化器
# train_step = tf.train.AdamOptimizer(1e-4).minimize(loss)
train_step = tf.train.MomentumOptimizer(1e-4, 0.9).minimize(loss)
# 评估模型
correct_prediction = tf.equal(tf.argmax(y_model, 1), tf.argmax(y_data, 1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float"))
init = tf.initialize_all_variables()
sess = tf.Session()
sess.run(init)
for _ in range(10):
for i in range(int(len(dataset) / 100)):
sess.run(train_step, feed_dict={x_data: dataset[i:i + 100, :], y_data: labless[i:i + 100, :]})
xl_weight = sess.run(weight)
W = np.dot(xl_weight, useranswer)
result = 0
for i in range(len(W[0])):
for j in range(len(W[0, :])):
if (i == j):
result += W[i][j]
result = int(result / 5)
if (result <= 3):
result = 3
elif (result <= 6):
result = 6
else:
result = 9
sql = "select ILL_NAME from ill_result_tbZ where FAMILY='%s' and ILL_ID=%d" % (surgeryChest, result)
cursor.execute(sql)
rows = cursor.fetchall()
ILL_NAME = []
for row in rows:
ILL_NAME.append(row[0])
firstResult = ILL_NAME[0]
if (firstResult[:2] == "疑似"):
firstResult = "疑似患病"
print(firstResult)
prescriptionInfoResult, healthResult = getSugessiones(surgeryChest, firstResult)
chufang = ''
for i in range(len(prescriptionInfoResult)):
chufang = chufang + '诊断处方' + str(i + 1) + '：' + prescriptionInfoResult[i] + '。'
print('诊断处方' + str(i + 1) + '：' + prescriptionInfoResult[i])
jianyi = ''
for i in range(len(healthResult)):
jianyi = jianyi + '养生建议' + str(i + 1) + '：' + healthResult[i] + '。'
print('养生建议' + str(i + 1) + '：' + healthResult[i])
if (firstResult != '正常'):
print("根据你的情况，系统推荐重点检查身体以下几项健康指标：")
seeproject = getSeeProject(surgeryChest)
print("推荐检查：", seeproject)
print("根据你的情况，系统向你推荐以下在这一治疗领域专家：")
doctorInfo = getDoctors(surgeryChest)
yisheng = ""
for i in range(len(doctorInfo)):
yisheng += doctorInfo[i]
print("===============================================================================================")
print("根据你所处的位置，系统找到以下与你距离最近的医院：")
yiyuaan = getPAH(province, administ)
sex = "男"
age = 13
addUser_SeeIll(userid, username, sex, age, province, administ, surgery, surgeryChest, firstResult, chufang,
jianyi, yiyuaan, yisheng, seeproject)
# zhenduan_n("1","2","3","4","4",6,"小东东","外科","胸外科","广东省","广州市")
# prescriptionInfoResult,healthResult = getSugessiones("胸外科","胸壁结核")
# a = getDoctors("胸外科")
# getPAH("广东省","广州市")
def action(infon):
zhenduan_n(int(infon[0]),int(infon[1]),int(infon[2]),int(infon[3]),int(infon[4]),int(infon[5]),infon[6],infon[7],infon[8],infon[9],infon[10])
if __name__ == '__main__':
infon = []
for i in range(1,len(sys.argv)):
infon.append(sys.argv[i])
action(infon)
