根据诊断依据标准词处理症状，并在症状后添加标准词

aipt-service/src/main/java/com/diagbot/facade/ClinicalFacade.java

@@ -7,29 +7,35 @@ import com.diagbot.client.bean.CalculateData;
 import com.diagbot.client.bean.GdbResponse;
 import com.diagbot.client.bean.Response;
 import com.diagbot.client.bean.ResponseData;
-import com.diagbot.dto.FeatureConceptDTO;
 import com.diagbot.dto.Lexeme;
 import com.diagbot.dto.LisResult;
 import com.diagbot.entity.ScaleContent;
-import com.diagbot.entity.SysLog;
 import com.diagbot.enums.ScaleTypeEnum;
 import com.diagbot.exception.CommonErrorCode;
 import com.diagbot.exception.CommonException;
 import com.diagbot.service.ScaleContentService;
-import com.diagbot.util.DateUtil;
 import com.diagbot.util.ListUtil;
 import com.diagbot.vo.SearchVo;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.stereotype.Component;
+import org.springframework.util.ResourceUtils;
 import org.springframework.web.bind.annotation.RequestBody;
 
+import java.io.BufferedReader;
+import java.io.File;
+import java.io.FileInputStream;
+import java.io.FileNotFoundException;
+import java.io.IOException;
+import java.io.InputStreamReader;
+import java.util.ArrayList;
+import java.util.HashMap;
 import java.util.List;
 import java.util.Map;
 import java.util.stream.Collectors;
 
 /**
  * <p>
- *  数据处理业务层
+ * 数据处理业务层
  * </p>
  *
  * @author Mark Huang
@@ -60,8 +66,9 @@ public class ClinicalFacade {
      */
     public ResponseData processClinicalData(@RequestBody SearchVo searchVo) {
         SearchVo sData = searchVo;
-
+        Map<String, List<Map<String, String>>> standWord = getStandWord();
         Response<List<Lexeme>> resp = nlpServiceClient.split(sData.getSymptom());
+        addStandWord(resp.getData(), standWord, searchVo);
 
         sData.setLisArr(processLis(sData.getLisArr()));
 
@@ -180,4 +187,230 @@ public class ClinicalFacade {
         }
         return response;
     }
+
+    public SearchVo addStandWord(List<Lexeme> lexemes, Map<String, List<Map<String, String>>> standWords, SearchVo sData) {
+        List<Lexeme> feature = new ArrayList<>();
+        //收集分词结果中体征指标或体征指标值（数字）
+        for (int i = 0; i < lexemes.size(); i++) {
+            if (lexemes.get(i).getProperty().contains("33") || lexemes.get(i).getProperty().contains("28")
+                    || lexemes.get(i).getProperty().contains("2") || lexemes.get(i).getProperty().contains("9")
+                    ) {
+                feature.add(lexemes.get(i));
+            }
+        }
+        //根据收集到的分词结果把体征指标和对应体征指标值（数字）拼接
+        List<String> featureType = new ArrayList<>();
+        for (int i = 0; i < feature.size(); i++) {
+            if (i < feature.size() - 1) {
+                try {
+                    if (feature.get(i).getProperty().contains("33") && feature.get(i + 1).getProperty().contains("28")) {
+                        featureType.add(feature.get(i).getText() + "\t" + feature.get(i + 1).getText());
+                    }
+                } catch (NumberFormatException e) {
+                    e.printStackTrace();
+                    System.out.println(e.getMessage());
+                }
+            }
+            if (i < feature.size() - 2) {
+                try {
+                    if ((feature.get(i).getProperty().contains("33") && feature.get(i + 1).getProperty().contains("28")
+                            && feature.get(i + 2).getProperty().contains("2"))
+                            || (feature.get(i).getProperty().contains("33") && feature.get(i + 1).getProperty().contains("28")
+                            && feature.get(i + 1).getProperty().contains("9"))) {
+                        featureType.add(feature.get(i).getText() + "\t" + feature.get(i + 1).getText() + "\t"
+                                + feature.get(i + 2).getText());
+                    }
+                } catch (NumberFormatException e) {
+                    e.printStackTrace();
+                    System.out.println(e.getMessage());
+                }
+            }
+        }
+        //将标准词中体征指标值（数字）与分词结果中体征指标值（数字）比较
+        for (String f : featureType) {
+            String[] features = f.split("\t");
+            if (standWords.containsKey(features[0])) {
+                List<Map<String, String>> standWordList = standWords.get(features[0]);
+                for (Map<String, String> standWordMap : standWordList) {
+                    if (standWordMap.containsKey("op") && standWordMap.containsKey("unit")
+                            && standWordMap.containsKey("value")) {
+                        if (features.length == 2) {
+                            judgment(sData, features, features[0], standWordMap);
+                        } else {
+                            if (standWordMap.get("unit").equals(features[2])) {
+                                judgment(sData, features, features[0], standWordMap);
+                            }
+                        }
+                    } else if (standWordMap.containsKey("op") && standWordMap.containsKey("value")) {
+                        if (features.length == 2) {
+                            judgment(sData, features, features[0], standWordMap);
+                        }
+                    }
+                }
+            }
+        }
+        return sData;
+    }
+
+    //将标准词中体征指标值（数字）与分词结果中体征指标值（数字）比较
+    private void judgment(SearchVo sData, String[] features, String standWordKey, Map<String, String> standWordMap) {
+        if (standWordMap.get("op").contains(">=") || standWordMap.get("op").contains("≥")
+                || standWordMap.get("op").contains(">") || standWordMap.get("op").contains("大于")
+                || standWordMap.get("op").contains("＞") || standWordMap.get("op").contains("大")) {
+            //单独处理  血压≥140/90mmHg   类似情况
+            if (features[1].contains("/")) {
+                if (standWordMap.get("value").contains("/")) {
+                    String[] feature = features[1].split("/");
+                    Integer featuresSBP = Integer.valueOf(feature[0]); //收缩压
+                    Integer featuresDBP = Integer.valueOf(feature[1]); //舒张压
+
+                    String[] values = standWordMap.get("value").split("/");
+                    Integer standWordSBP = Integer.valueOf(values[0]); //收缩压
+                    Integer standWordDBP = Integer.valueOf(values[1]); //舒张压
+                    if (featuresSBP > standWordSBP && featuresDBP > standWordDBP) {
+                        String standWord = standWordKey + standWordMap.get("op") + standWordMap.get("value") + standWordMap.get("unit") + "。";
+                        sData.setSymptom(sData.getSymptom() + standWord);
+                        System.out.println(sData.getSymptom());
+                    } else {
+                        return;
+                    }
+                } else {
+                    return;
+                }
+            } else {
+                String num = getNum(standWordMap.get("value"));
+                if (Double.valueOf(getNum(features[1])) > Double.valueOf(num)) {
+                    String standWord = standWordKey + standWordMap.get("op") + standWordMap.get("value") + standWordMap.get("unit") + "。";
+                    sData.setSymptom(sData.getSymptom() + standWord);
+                    System.out.println(sData.getSymptom());
+
+                }
+            }
+        } else if (standWordMap.get("op").contains("<=") || standWordMap.get("op").contains("≤")
+                || standWordMap.get("op").contains("<") || standWordMap.get("op").contains("小于")
+                || standWordMap.get("op").contains("＜") || standWordMap.get("op").contains("少于")
+                || standWordMap.get("op").contains("小")) {
+            //单独处理  血压小于90/60mmHg   类似情况
+            if (standWordMap.get("value").contains("/")) {
+                if (features[1].contains("/")) {
+                    String[] feature = features[1].split("/");
+                    Integer featuresSBP = Integer.valueOf(feature[0]); //收缩压
+                    Integer featuresDBP = Integer.valueOf(feature[1]); //舒张压
+
+                    String[] values = standWordMap.get("value").split("/");
+                    Integer standWordSBP = Integer.valueOf(values[0]); //收缩压
+                    Integer standWordDBP = Integer.valueOf(values[1]); //舒张压
+                    if (featuresSBP < standWordSBP && featuresDBP < standWordDBP) {
+                        String standWord = standWordKey + standWordMap.get("op") + standWordMap.get("value") + standWordMap.get("unit") + "。";
+                        sData.setSymptom(sData.getSymptom() + standWord);
+                        System.out.println(sData.getSymptom());
+                    } else {
+                        return;
+                    }
+                } else {
+                    return;
+                }
+            } else {
+                String num = getNum(standWordMap.get("value"));
+                if (Double.valueOf(getNum(features[1])) < Double.valueOf(num)) {
+                    String standWord = standWordKey + standWordMap.get("op") + standWordMap.get("value") + standWordMap.get("unit") + "。";
+                    sData.setSymptom(sData.getSymptom() + standWord);
+                    System.out.println(sData.getSymptom());
+                }
+            }
+        }
+    }
+
+    private String getNum(String standWord) {
+        StringBuffer sb = new StringBuffer();
+        try {
+            for (String num : standWord.replaceAll("[^0-9]", ",").split(",")) {
+                if (num.length() > 0) {
+                    sb.append(num);
+                }
+            }
+        } catch (NumberFormatException e) {
+            e.printStackTrace();
+        }
+        return sb.toString();
+    }
+
+    private Map<String, List<Map<String, String>>> getStandWord() {
+        Map<String, List<Map<String, String>>> standWordObj = new HashMap<>();
+        List<List<Lexeme>> splitStandWords = new ArrayList<>();
+        List<Lexeme> data = null;
+        File file = null;
+        BufferedReader reader = null;
+        String line = "";
+        try {
+            file = ResourceUtils.getFile("classpath:standword.txt");
+            reader = new BufferedReader(new InputStreamReader(new FileInputStream(file), "UTF-8"));
+            while ((line = reader.readLine()) != null) {
+                data = nlpServiceClient.split(line).getData();
+                splitStandWords.add(data);
+                //                standWord.add(line);
+            }
+        } catch (FileNotFoundException e) {
+            e.printStackTrace();
+        } catch (IOException e) {
+            e.printStackTrace();
+        } finally {
+            try {
+                reader.close();
+            } catch (IOException e) {
+                e.printStackTrace();
+            }
+        }
+        List<Map<String, String>> standWordObjValList = null;
+        Map<String, String> standWordObjVal = null;
+        for (List<Lexeme> splitStandWord : splitStandWords) {
+            standWordObjValList = new ArrayList<>();
+            standWordObjVal = new HashMap<>();
+            int i = 0;
+            String standWordObjKey = "";
+            for (Lexeme lexeme : splitStandWord) {
+                i++;
+                if ("\uFEFF".equals(lexeme.getText()) || lexeme.getText().length() <= 0) {
+                    continue;
+                }
+                if (lexeme.getProperty().contains("1") || lexeme.getProperty().contains("5")
+                        || lexeme.getProperty().contains("33")) {
+
+                    if (!standWordObj.containsKey(lexeme.getText())) {
+                        standWordObj.put(lexeme.getText(), standWordObjValList);
+                    } else {
+                        standWordObjKey = lexeme.getText();
+                    }
+                } else if (lexeme.getProperty().contains("44")) {
+
+                    if (standWordObjVal.containsKey("op")) {
+                        standWordObjVal.put("op", standWordObjVal.get("op") + "," + lexeme.getText());
+                    } else {
+                        standWordObjVal.put("op", lexeme.getText());
+                    }
+                } else if (lexeme.getProperty().contains("13") || lexeme.getProperty().contains("28")) {
+                    if (standWordObjVal.containsKey("value")) {
+                        standWordObjVal.put("value", standWordObjVal.get("value") + "," + lexeme.getText());
+                    } else {
+                        standWordObjVal.put("value", lexeme.getText());
+                    }
+                } else if (lexeme.getProperty().contains("2") || lexeme.getProperty().contains("9")) {
+                    if (standWordObjVal.containsKey("unit")) {
+                        standWordObjVal.put("unit", standWordObjVal.get("unit") + "," + lexeme.getText());
+                    } else {
+                        standWordObjVal.put("unit", lexeme.getText());
+                    }
+                }
+                if (splitStandWord.size() == i) {
+                    if (standWordObj.containsKey(standWordObjKey)) {
+                        standWordObj.get(standWordObjKey).add(standWordObjVal);
+                    } else {
+                        standWordObjValList.add(standWordObjVal);
+                    }
+                }
+            }
+        }
+        return standWordObj;
+    }
+
 }

aipt-service/src/main/resources/standword.txt

@@ -0,0 +1,51 @@
+排便少于每周3次
+布氏征阳性
+附件活动性包块
+收缩压≥140mmHg
+收缩压大于140mmHg
+舒张压≥90mmHg
+舒张压大于90mmHg
+血压大于140mmHg
+悬壅垂水肿
+腰/臀比例＞0.85
+血压≥140/90mmHg
+胎体
+不规则阴道出血/阴道出血
+下腹肿块/腹块
+心率大于100次/分
+口咽黏膜弥漫性充血肿胀
+悬壅垂水肿
+悬壅垂水肿
+血压小于90/60mmHg
+胸痛持续时间大于10分钟
+悬壅垂水肿
+电解质检查
+肺功能检查
+淋巴结细胞学检查
+腹部彩超
+膝关节痛风石
+触觉语颤增强
+晨僵≥30分钟
+BMI小于21
+体重指数小于21
+右上腹部饱满
+胃脱落细胞学检查
+肢体活动受限
+DBP＞90mmHg
+SBP＞140mmHg
+收缩压＞140mmHg
+舒张压＞90mmHg
+血压＞140/90mmHg
+心率>90次/分
+R＞20次/分
+体温＜36℃
+体温＞38℃
+R≥24次/分钟
+呼吸频率大于24次/分钟
+Hachinski缺血积分＜4分
+Hachinski评分＜4分
+HIS缺血指数＜4分
+HIS评分＜4分
+关节僵硬＜30min
+晨僵＜30min
+肢体苍白