A medical assistive device for quick positioning which can be combined with surgical reduction forceps rapidly, free from angle limitation, operated more conveniently. It comprises a base, the top surface thereof can hold the patient's wrist region; a socket holder located under the bottom surface of the base, provided with a round cavity-like hole slot; multiple support columns vertically located on the bottom surface of the base, surrounding the socket holder, forming connected passages under the base; a universal joint, embedded in the hole slot of socket holder, flexibly diverted. Thereby, the lower forceps body of surgical reduction forceps can reach the lower part of socket holder at any angle under the base, so that the lower forceps body is combined with the universal joint quickly, the combination is rapid, and the lower forceps body can rotate flexibly.

A method for predicting epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma is provided. The method utilizes a lung adenocarcinoma EGFR mutation classification model based on a deep learning model, and performs back-propagation training on the deep learning model by using whole-slide pathological images and corresponding pathological data. The trained lung adenocarcinoma EGFR mutation classification model can determine whether a to-be-classified slide-level image with lung adenocarcinoma features have EGFR mutations.

The present disclosure provides an operation method of a PET (positron emission tomography) quantitative localization system, which includes steps as follows. The PET image and the MRI (magnetic resonance imaging) of the patient are acquired; the nonlinear deformation is performed on the MRI and the T1 template to generate deformation information parameters; the AAL (automated anatomical labeling) atlas is deformed to an individual brain space of the patient, so as to generate an individual brain space AAL atlas, where the AAL atlas and the T1 template are in a same space; lateralization indexes of the ROIs of the individual brain space AAL atlas corresponding to the PET image normalized through the gray-scale intensity are calculated; the lateralization indexes are inputted into one or more machine learning models to analyze the result of determining a target.

提供一種能提高判讀精確度之X光片內組織尺寸的量測方法。

以即時掌握心肺功能異常之病患的行動資訊以供後續即時處置與判斷之居家照護系統

一種可提供患有心衰竭疾病之病患、學術人員與供應商進行線上聯繫之醫療照護互聯網平台

採集病人的正子攝影影像與磁振造影影像；將磁振造影影像與T1模板進行非線性變形空間對位以產生變形資訊參數；將與T1模板相同空間的自動化解剖標記（AAL）圖譜以變形資訊參數轉換至病人的個人腦空間以產生個人腦空間AAL圖譜；計算灰階強度標準化後的正子攝影影像對應於個人腦空間AAL圖譜的複數個感興趣區域的複數個側向指數；將複數個側向指數輸入機器學習模型，以分析機器學習模型判定預設目標的結果。

提供一種藉由量測聲音、震動、及位移的結果以監看呼吸的態樣的生理監測設備。

提供一種藉由量測聲音、震動、及位移的結果以監看呼吸的態樣的生理監測設備。

提供一種藉由量測聲音、震動、及位移的結果以監看呼吸的態樣的生理監測設備。

現有技術的不足提供一種用於預測肺腺癌是否具有表皮生長因子受體突變的方法。

一種用於預測肺腺癌是否具有表皮生長因子受體突變的方法，採用基於一深度學習模型的一肺腺癌EGFR突變分類模型，並使用全玻片病理影像及對應的病理資料對深度學習模型進行倒傳遞訓練。

一種用於預測癌症之電腦實施方法。該電腦實施方法包括：自資料庫中擷取使用者的電子病歷；將該電子病歷轉換為矩陣；並且根據癌症預測模型判定與該矩陣相對應的癌症預測結果。

針對現有技術的不足提供一種可提升分離癌細胞及非癌細胞區域的效果的用於癌症病灶的視覺化方法。

提供一種能透過一偵測評估系統自動評估患者的吸氣與吐氣狀態，從而利用X光片評估呼吸狀態的方法。

提供一種能透過一偵測評估系統自動評估患者的吸氣與吐氣狀態，從而利用X光片評估呼吸狀態的方法。

提供一種能透過一偵測評估系統自動評估患者的吸氣與吐氣狀態，從而利用X光片評估呼吸狀態的方法。

提供一種能透過一偵測評估系統自動評估患者的吸氣與吐氣狀態，從而利用X光片評估呼吸狀態的方法。

提供一種使用擴增實境訓練日常生活功能之系統，所謂擴增實境（Augmented Reality，簡稱AR），是指透過攝影機影像的位置及角度精算並加上圖像分析技術，讓螢幕上的虛擬世界能夠與現實世界場景進行結合與互動的技術。

一種治療劑篩檢方法，該方法包含下列步驟：首先，自一脊椎動物獲得一椎間盤，並以一第一無菌溶液處理該椎間盤。接著，將一分解溶液注射至該椎間盤，以去除該椎間盤的部分中央髓核組織。