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The Kissing Bug

為了解決Apple healthcare的問題，作者Hernández, Daisy 這樣論述：

Growing up in a New Jersey factory town in the 1980s, Daisy Hernández believed that her aunt had become deathly ill from eating an apple. No one in her family, in either the United States or Colombia, spoke of infectious diseases. Even into her thirties, she only knew that her aunt had died of Ch

agas, a rare and devastating illness that affects the heart and digestive system. But as Hernández dug deeper, she discovered that Chagas--or the kissing bug disease--is more prevalent in the United States than the Zika virus. After her aunt’s death, Hernández began searching for answers. Crisscross

ing the country, she interviewed patients, doctors, epidemiologists, and even veterinarians with the Department of Defense. She learned that in the United States more than three hundred thousand people in the Latinx community have Chagas, and that outside of Latin America, this is the only country w

ith the native insects--the ＂kissing bugs＂--that carry the Chagas parasite.Through unsparing, gripping, and humane portraits, Hernández chronicles a story vast in scope and urgent in its implications, exposing how poverty, racism, and public policies have conspired to keep this disease hidden. A riv

eting and nuanced investigation into racial politics and for-profit healthcare in the United States, The Kissing Bug reveals the intimate history of a marginalized disease and connects us to the lives at the center of it all.

Apple healthcare進入發燒排行的影片

足底壓力影像處理設計應用於深度學習

為了解決Apple healthcare的問題，作者PETER ARDHIANTO 這樣論述：

足底壓力圖像涉及評估和診斷足部問題。放射科專家執行手動分析和檢測，以根據足底圖像評估足部問題。近年來的深度學習使醫療人員能夠根據足底壓力圖像自動檢測疾病。此外，圖像設計是基於足底壓力圖像提高深度學習性能的有用策略。足底成像揭示了足部在平衡和運動過程中的機械行為和輪廓。而腦性麻痺患者，具有導致足底壓力缺陷。異常的足底壓力可能會限制腦性麻痺患者的左右腳識別，例如具有異常足部前進角度的剪刀步態，和具有缺陷足底壓力的腳趾行走。本研究探討了足底壓力圖像改進的設計，以識別左腳和右腳，並使用各種對象檢測模型預測“足部前進角度“ ，以獲得基於足底壓力圖像數據集的合適檢測器。結果表明，YOLOv4 在區分左腳

和右腳，以及從足底壓力圖像預測“足部前進角度 ”方面表現出色。在各種矩陣中，YOLOv4 的表現優於不同的模型。右腳預測高於左腳。使用 YOLOv4 進行深度學習可增強 “足部前進角度“ 預測，而不會顯著偏離基本事實（5.58 ± 0.10° vs. 5.86 ± 0.09°，p = 0.013）。 ground truth 的” 足部前進角度” 與 YOLOv3（5.58 ± 0.10° vs. 6.07 ± 0.06°，p < 0.001）和 ground truth 的 “足部前進角度” vs. YOLOv5x（5.58±0.10° vs. 6.75 ± 0.06°，p < 0.001）

有顯著差異。此外，準確的左右識別和“ 足部前進角度“ 的預測可以提供有關足部的信息。左右腳的自動檢測，可能會對具有 腦性麻痺特徵的不正常足底壓力圖像產生影響，並為管理優勢肢矯形器治療提供重要信息。

Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics

為了解決Apple healthcare的問題，作者 這樣論述：

Abhishek Kumar is Doctorate in computer science from University of Madras and done M.tech in Computer Sci. & Engineering from Government engineering college Ajmer, Rajasthan Technical University, Kota India. He has total Academic teaching experience of more than 7 years with more than 80 publication

s in reputed, peer reviewed National and International Journals, books & Conferences. He has guided more than 20 M.Tech Projects and Thesis and guiding 2 PhD Scholar. His research area includes- Artificial intelligence, Image processing, Computer Vision, Data Mining, Machine Learning. He has been Se

ssion chair and keynote Speaker of many International conferences, webinars in India and Abroad. He has been the reviewer for IEEE and Inderscience Journal. He has authored/Co-Authored 6 books published internationally and edited 16 book (Published & ongoing with Elsevier, Wiley, IGI GLOBAL Springer

, Apple Academic Press, De-Grueter and CRC etc. He has been member of various National and International professional societies in the field of engineering & research like Senior Member of IEEE, IAENG (International Association of Engineers), Associate Member of IRED (Institute of Research Engineers

and Doctors), He has got Sir CV Raman National award for 2018 in young researcher and faculty Category from IJRP Group. He is Editor of Special issue in the Journal Computer materials and continua [SCI and SCOPUS.IF- 4.98] and Intelligent Automation and Soft Computing [SCI, SCOPUS, IF-1.276] Cognit

ive Neuro dynamics, Springer [SCI, SCOPUS, IF-3.925].Anavatti G. Sreenatha is a Senior Lecturer with the School of Engineering and Information Technology at the University of New South Wales, Canberra, Australia. He has a Ph.D. from Indian Institute of Science, Bengaluru, India. Before moving to Aus

tralia, he was an Associate Professor at Indian Institute of Technology, Mumbai, India. As an established faculty at Indian Institute of Technology, he has contributed to the major National Projects like Indian Remote Sensing Satellite, Light Combat Aircraft and Air to Air Missile. His research work

includes the application of AI for autonomous systems that include image processing for improved sensing and GAN based networks for improved classification with imbalanced data sets. In addition, he also works on the application of modern control tools for applications related to Aerospace, Underwa

ter and Ground Vehicles including Evolutionary Fuzzy and Fuzzy Neural Systems for identification and control of dynamic systems. He has authored more than 250 papers in peer reviewed International Journals and International conferences. He has been an active reviewer for a number of high quality jou

rnals like IEEE transactions and Technical Committee member for a number of International Conferences like SSCIAshutosh Kumar Dubey PhDis currently in the department of Computer Science and Engineering, Chitkara University School of Engineering and Technology, Chitkara University, Himachal Pradesh,

India. He received his PhD degree in Computer Science and Engineering from JK Lakshmipat University, Jaipur, and Rajasthan, India. He is the Senior Member of IEEE and ACM. He has more than 14 years of teaching experience. He has authored a book name Database Management Concepts. He has been associat

ed with many international and national conferences as the Technical Program Committee member. He is also associated as the Editor/Editorial Board Member/ Reviewer of many peer-reviewed journals. His research areas are Data Mining, Health Informatics, Optimization, Machine Learning, Cloud Computing,

Artificial Intelligence and Object-Oriented Programming.Pramod Singh Rathore is pursuing his Doctorate in computer science from University of Engineering and Management (UEM) and done M. Tech in Computer Sci. & Engineering from Government engineering college Ajmer, Rajasthan Technical University, K

ota India. He has been working as an Assistant professor of Computer Science & Engineering Department at Aryabhatt Engineering College and Research centre, Ajmer, Rajasthan and also visiting faculty in Government University MDS Ajmer. He has total Academic teaching experience of more than 8 years wi

th more than 50 publications in reputed, peer reviewed National and International Journals, books & Conferences like Wiley, IGI GLOBAL, Taylor & Francis Springer, Elsevier Science Direct, Annals of Computer Science, Poland, and IEEE. He has authored/Co-Authored 6 books published internationally and

edited 16 book (Published & ongoing with Elsevier, Wiley, IGI GLOBAL Springer, Apple Academic Press, De-Grueter and CRC etc. His research area includes NS2, Computer Network, Mining, and DBMS.

高齡者健康智慧衣之設計與應用研究

為了解決Apple healthcare的問題，作者賴靜儀 這樣論述：

摘要 iAbstract ii誌謝 iii目錄 iv表目錄 viii圖目錄 ix第一章 緒論 11.1研究背景與動機 11.1.1研究背景 11.1.2研究動機 21.2 研究目的 21.3研究範圍與限制 21.3.1研究範圍 21.3.2研究限制 31.4研究流程 41.5 論文架構 5第二章 文獻探討 62.1高齡者的相關研究 62.1.1高齡者身心特徵相關研究 62.1.2照護高齡者的概況分析研究 72.2導電材料與設備相關研究 72.2.1 導電材料銀纖維 72.2.2 導電布織造 82.2.3市售凝膠電極貼片 102.2.4量測生理

數據設備 102.3高齡者的服裝設計相關研究 112.3.1 高齡者服裝特點 112.3.2 服裝的三大要素 122.3.3高齡者服裝的舒適性 132.3.4 高齡者的服裝尺碼標準 132.4健康智慧衣應用範圍研究 142.4.1 智慧衣的需求 142.4.2心律生理數據 142.4.3照護型智慧衣 162.5小結 17第三章 導電材料適用性與健康智慧衣設計之實驗研究 193.1第一階段：受測環境與儀器穩定度之實驗 203.1.1研究方法 203.1.2資料分析 203.1.3實驗結果與討論 213.2第二階段：導電材料適用性之實驗量測 213.2.1研究方法

213.2.2數據分析 223.2.3實驗結果與討論 233.3第三階段：健康智慧衣設計 243.3.1健康智慧衣設計概念發想 243.3.2健康智慧衣製作實施步驟 253.3.3健康智慧衣試穿 273.3.4研究結果與討論 28第四章 健康智慧衣應用在高齡者的使用需求調查與分析 294.1第一階段：協助高齡者穿著健康智慧衣狀況調查(照護者) 314.1.1 研究方法 314.1.2研究對象：居家照護者 314.1.3調查內容 324.1.4數據分析 334.1.5 現況調查結果 344.1.6訪談結果 354.1.7研究結果與討論 384.2 第二階段：健

康智慧衣S/M/L尺寸心律適性比較(高齡者) 384.2.1 研究方法 384.2.2招募方式 384.2.3 實驗過程 394.2.4數據分析 394.2.5 研究結果與討論 404.3第三階段：健康智慧衣與凝膠使用評估比較(高齡者) 404.3.1 研究方法 414.3.2招募方式 414.3.3 實驗過程 414.3.4數據分析 444.3.5高齡者使用性及主觀滿意度問卷評估 484.3.6數據分析 484.3.7健康智慧衣問卷評估結果 534.3.8健康智慧衣改善設計要點 534.3.9 研究結果與討論 564.4 第四階段：改善設計後健康智慧衣使用調查

評估(高齡者) 574.4.1 研究方法 574.4.2 研究對象:高齡者 574.4.3調查過程 574.4.4改善設計後健康智慧衣調查評估 574.4.5數據分析 584.4.6 研究結果與討論 61第五章 結論 655.1 研究結論 655.2 未來研究方向 66文獻參考 67附錄 75附錄一【高齡者健康智慧衣之設計與應用研究】受試者同意書 75附錄二【高齡者健康智慧衣之設計與應用研究-高齡者試穿】問卷調查表 77附錄三【高齡者健康智慧衣之設計與應用研究】照護者問卷訪談同意書 79附錄四【高齡者健康智慧衣之設計與應用研究-照護者】問卷調查表 81附錄五【

高齡者改善設計後健康智慧衣之設計與應用研究】受試者同意書 83附錄六【高齡者改善設計後健康智慧衣】問卷調查表 85附錄七【銀纖布SGS測試報告無重金屬認證】 87附錄八【虹泰"電極貼片規格說明】 89附錄九【MAX30003 MAX-ECG-MONITOR操作手冊說明】 91附錄十【實驗操作儀器設備介紹】 95附錄十一【健康智慧衣製作實施步驟】 96附錄十二【中華民國專利發明I717234證書】 104附錄十三【中華民國新型專利健康智慧衣的結構裝置申請書】 105