查詢結果分析
來源資料
頁籤選單縮合
| 題 名 | 建構智慧中醫及應用模式計畫=Smart Chinese Medicine and Application Mode Building Project |
|---|---|
| 作 者 | 黃升騰; | 書刊名 | 中醫藥年報 |
| 卷 期 | 12 2023.10[民112.10] |
| 頁 次 | 頁(2)1-(2)51 |
| 分類號 | 413.91 |
| 關鍵詞 | 虛擬實境; 針灸; 經絡; 大數據; 中醫; 大腸癌; Virtual reality; Acupuncture; Meridian; Big data analysis; Chinese medicine; Colorectal cancer; |
| 語 文 | 中文(Chinese) |
| 中文摘要 | 研究目的: 針灸為中醫的特殊治療手段,雖然針灸與經絡的相關記載已有千年以上, 但學習的方式與現今並無太大的變化。除了依靠文字與圖譜,操作的學習主 要以模型—也就是大家耳熟能詳的銅人,或是以師徒制的方式由資深醫師 手把手教學與傳承。然而,我們希望開創全新的教學方式進一步提升針灸教 育的成效。 研究方法: 我們整理世界衛生組織公布的標準針灸經穴定位一書中,有關針灸穴位 的資料,再與○○○ (D****)和○○○○ (D******)兩家公司合作開發虛擬 實境針灸教學模型,藉以訓練學生各穴位的取穴位置、有效穴位、行針手法、 禁忌症以及進行穴位安全深度訓練,可利用此一模型設計基本穴位認識、測 驗、情境模擬以加強學習成效。 此外,大腸癌是世界第三大癌症,也是臺灣男性排名第一、女性排名第 二的癌症。隨著中醫治療大腸癌病人的病歷逐漸累積,不管是醫案書籍或是 院內病歷,皆產出大量資料。因此,我們會藉用 D********公司的技術,將 醫案書籍中的病歷資料,利用光學字元辨識和文本探勘技術萃取出來,再使 用其公司藉由 14 萬筆病歷,並運用自然語言處理和類神經網路技術製作而 成的模型,將複雜的中醫詞彙標準化。接著將院內接受過中醫治療的大腸癌 病歷調出,同樣經過標準化。最後,將書籍、院內中醫病歷資料,與○○○ ○○○協會(C***)合作利用變異數和集群分析交叉比對,找出中醫對大腸癌 的主要證型,並與健保資料庫的中藥比對。結果與討論: 我們發現大腸癌的病人主要分成(因機密刪除)五種證型,依照不同頻率 分布在(因機密刪除)群病人身上。而這些證型分析結果,亦與臺灣中醫師面 對大腸癌病人的開藥思路相符。這樣的結果可提供臨床中醫師在面對大腸 癌病人時參考使用。 |
| 英文摘要 | Aim: Acupuncture is a distinct therapy of traditional Chinese medicine. As we know, acupuncture associated with meridians is known more than one thousand years, however, the learning process was never changed. It is still learned by word records, pictures and bronze acupuncture figures. Additionally, senior tutors are essential for acupuncture teaching for students step by step. Thus, we are trying to create a brand-new system for acupuncture education and speed up the effectiveness of learning. Method: We compiled data from 《WHO standard acupuncture point locations》, and established acupuncture education model in virtual reality system with two companies D**** and D****** respectively. We also trained the model about acupoint locations, manipulations of acupuncture, indications, contraindications and safety depth of acupoints. Basic acupoints knowledge to simulation of clinical situations was also programmed. Colorectal cancer (CRC) is the third popular cancer in the world. It is the number one cancer in Taiwanese men and the second popular in Taiwanese women. So far, with the accumulation of medical records in patients with CRC treated by TCM archived in TCM books or in the hospital, a huge amount of cases was created. Thus, we are trying to standardize the medical records, and build the database of TCM of CRC cases for further investigation. First, D******** technology by using Optical character recognition and Text-mining techniques was applied to extract medical records from TCM books. We used this model to standardize TCM terms. This model is originated from more than 140,000 TCM cases with Natural Language Processing and Neural Network techniques processing. Second, we collected the CRC records with TCM treatment in CMU hospital to standardize by D******** technology. Finally, we collaborated with Chung-huo Data Mining Society to analysis all of data with ANOVA and Cluster Analysis. Results & Discussion: We found that patients with colorectal cancer are mainly divided into five types of patterns: (因機密刪除), which are distributed in four clusters of patients with different frequencies. The results of the analysis of these syndrome types are also consistent with the thinking of Taiwanese Chinese physicians to prescribe drugs for patients with colorectal cancer. This result can be used as a reference for clinicians when facing patients with colorectal cancer. |
本系統中英文摘要資訊取自各篇刊載內容。