diff --git a/.gitignore b/.gitignore
index 7c5f526..1834aff 100644
--- a/.gitignore
+++ b/.gitignore
@@ -212,10 +212,10 @@ log/*
 example/*
 !example/readme.md
 
-xlsx/*
+/xlsx/
 !xlsx/readme.md
 
-result/*docx
+/result/
 !result/readme.md
 
 /.report/
\ No newline at end of file
diff --git a/result/2023WSSW000709-T.docx b/result/2023WSSW000709-T.docx
index 581e43d..aa64dab 100644
Binary files a/result/2023WSSW000709-T.docx and b/result/2023WSSW000709-T.docx differ
diff --git a/tools/parsexlsx.py b/tools/parsexlsx.py
index b3d9680..c612951 100644
--- a/tools/parsexlsx.py
+++ b/tools/parsexlsx.py
@@ -172,109 +172,6 @@ class Parse(BaseAssignment):
     def msi(self):
         self._to_dicts('MSI')
 
-    # def chemo(self):
-    #     data = pd.DataFrame(self.sampledata['chemo'])
-    #
-    #     project = data['project'].to_list()[0]
-    #
-    #     # 分类汇总 同位点，药物合并 drug.infos.txt
-    #     drugrsid = data[['drugname', 'genename', 'rsid', 'result', 'level', 'tips', 'drugsort']]
-    #     drugrsid = drugrsid.drop_duplicates()
-    #     resdrugrsid = drugrsid.groupby(['drugname', 'genename', 'rsid', 'result', 'level', 'drugsort'])['tips'].agg(
-    #         ','.join).reset_index()
-    #     resdrugrsid.rename(columns=
-    #                        {'drugname': '药物', 'genename': '检测基因', 'rsid': '检测位点', 'result': '基因型',
-    #                         'level': '证据等级', 'tips': '用药提示'},
-    #                        inplace=True)
-    #     resdrugrsid = resdrugrsid.sort_values(by=['drugsort', '药物', '检测基因'])
-    #     self.result['chemo']['druginfo'] = resdrugrsid.to_dict('records')
-    #
-    #     # 药物 药物疗效 推荐程度合并 drug.res.txt
-    #     drugtypesum = data[['drugname', 'drugtype', 'rsid', 'weights']]
-    #     drugtypesum = drugtypesum.drop_duplicates()
-    #     drugtyperes = list()
-    #     drugsum = dict()
-    #     for drug, drugdata in drugtypesum.groupby('drugname'):
-    #         tipsnum = drugdata.groupby(['drugtype']).agg({'weights': 'sum'}).to_dict('index')
-    #         sumlist = list()
-    #         if 'LX' in tipsnum:
-    #             LX = tipsnum['LX']['weights']
-    #             if LX > 0:
-    #                 lxdes = '疗效较好'
-    #                 lxnum = 1
-    #             elif LX == 0:
-    #                 lxdes = '疗效一般'
-    #                 lxnum = 0
-    #             else:
-    #                 lxdes = '疗效较差'
-    #                 lxnum = -1
-    #             sumlist.append(lxdes)
-    #         else:
-    #             LX = 0
-    #             lxnum = 0
-    #         if 'DF' in tipsnum:
-    #             DF = tipsnum['DF']['weights']
-    #             if DF > 0:
-    #                 dfdes = '毒副较低'
-    #                 dfnum = 1
-    #             elif DF == 0:
-    #                 dfdes = '毒副一般'
-    #                 dfnum = 0
-    #             else:
-    #                 dfdes = '毒副较高'
-    #                 dfnum = -1
-    #             sumlist.append(dfdes)
-    #         else:
-    #             DF = 0
-    #             dfnum = 0
-    #
-    #         # 评价方式 疗效 1 0 -1, 毒副 1 0 -1 ，可形成9宫格
-    #         sumnum = lxnum + dfnum
-    #         if sumnum > 0:
-    #             sumdes = '推荐'
-    #         elif sumnum == 0:
-    #             sumdes = '常规'
-    #         else:
-    #             sumdes = '谨慎'
-    #
-    #         # 特别药物处理
-    #         if (drug == "氟尿嘧啶" or drug == "卡培他滨") and DF < 0:
-    #             sumdes = '谨慎'
-    #
-    #         drugtyperes.append(dict(
-    #             药物名称=drug,
-    #             疗效=LX,
-    #             毒副=DF,
-    #             推荐程度=sumdes,
-    #             疗效和毒副总结=','.join(sumlist)
-    #         ))
-    #         drugsum[drug] = sumdes
-    #
-    #     # 报告中展示药物有顺序
-    #     drugsort = data[['drugname', 'drugsort']].drop_duplicates()
-    #     drugsort_dict = drugsort.set_index('drugname')['drugsort'].to_dict()
-    #     drugtyperes_sort = sorted(drugtyperes, key=lambda x: (
-    #         drugsort_dict[x['药物名称']] if x['药物名称'] in drugsort_dict else 100, x['药物名称']))
-    #
-    #     drugtyperes_sort_df = pd.DataFrame(drugtyperes_sort)
-    #     self.result['chemo']['sum'] = drugtyperes_sort_df.groupby('推荐程度')['药物名称'].apply(','.join).to_dict()
-    #     self.result['chemo']['drugres'] = drugtyperes_sort_df.to_dict('records')
-    #
-    #     # 联合用药
-    #     drug_combine_path = os.path.join(os.path.dirname(os.path.dirname(__file__)), 'database',
-    #                                      'chemo_drug_combine.csv')
-    #     drug_combine = pd.read_csv(drug_combine_path, sep='\t')
-    #     drug_combine.fillna('.', inplace=True)
-    #     drug_combine_data = drug_combine[drug_combine['source'].str.contains(project)]
-    #     drug_combine_data = drug_combine_data.reset_index()
-    #     if not drug_combine_data.empty:
-    #         drug_combine_data['临床提示'] = drug_combine_data['用药方案'].apply(self._get_drug_plan, args=(drugsum,))
-    #         self.result['chemo']['combine'] = drug_combine_data.groupby('癌种').apply(
-    #             lambda group: group.set_index('癌种').to_dict('records')).to_dict()
-    #     else:
-    #         self.result['chemo']['combine'] = dict()
-    #     self.result['sum']['chemo_drug_num'] = len(drugsum.keys())
-
     def chemo(self):
         chemo_res = self._to_records('chemo_res', need=True)
 
@@ -354,7 +251,7 @@ class Parse(BaseAssignment):
         if not data.empty:
             data = data.dropna()
             data = data[data['drug_detail'] != '.']
-            data = data.applymap(lambda x: str(x).replace('\\\\', '\n') if ' \\\\' in str(x) else x)
+            data = data.applymap(lambda x: str(x).replace('||', '\n') if '||' in str(x) else x)
             res = data.set_index('drug_name')['drug_detail'].to_dict()
         self.result['drugs']['drugs_detail'] = res
 
@@ -449,24 +346,6 @@ class Parse(BaseAssignment):
         #             self.drugs_record['drugs'].update({match.group(1).strip(): match.group(2).strip()})
         return drug_category_res
 
-    @staticmethod
-    def _get_drug_plan(x, drugsum):
-        tlist = x.split('+')
-        tdeslist = list()
-        for tdes in tlist:
-            if tdes.strip() in drugsum:
-                t1_des = drugsum[tdes.strip()]
-                tdeslist.append(t1_des)
-
-        if '慎用' in tdeslist or '谨慎' in tdeslist:
-            return '慎用'
-        elif '推荐' in tdeslist:
-            return '推荐'
-        elif '常规' in tdeslist:
-            return '可选'
-        else:
-            return '可选'
-
     def collect(self):
         self.cms()
         self.target()