歡迎來到演算法、軟體和硬體三位一體的未來世界論文書籍站
Diagnostic algorithm的問題，透過圖書和論文來找解法和答案更準確安心。 我們找到下列懶人包和總整理
Diagnostic algorithm的問題，我們搜遍了碩博士論文和台灣出版的書籍，推薦Singh Kuntal, Ravinder,Gupta, Radha,Rajendran, D.寫的 Livestock Ration Formulation for Dairy Cattle and Buffalo 和Rabbee, Nusrat的 Biomarker Analysis in Clinical Trials with R都 可以從中找到所需的評價。
這兩本書分別來自 和所出版 。
國立高雄科技大學 電子工程系 蘇德仁所指導 蔡智宇的 卷積神經網路結合模糊演算法應用於陰道鏡檢之 子宮頸上皮內贅瘤輔助診斷 （2021），提出Diagnostic algorithm關鍵因素是什麼，來自於卷積神經網路、模糊演算法、子宮頸上皮內贅瘤、陰道鏡檢查。
而第二篇論文國立雲林科技大學 工業工程與管理系 傅家啟所指導 丁俞文的 級聯 YOLO 與巢狀 U 型卷積神經網路之超參數優化於腦脊髓液磁振影像切割 （2021），提出因為有 自發性顱內低壓、腦脊髓液關注區域偵測、腦脊髓液分割、YOLO、巢狀U型卷積神經網路的重點而找出了 Diagnostic algorithm的解答。
除了Diagnostic algorithm，大家也想知道這些：
Livestock Ration Formulation for Dairy Cattle and Buffalo
為了解決Diagnostic algorithm 的問題，作者Singh Kuntal, Ravinder,Gupta, Radha,Rajendran, D. 這樣論述：
Dr Ravinder Singh Kuntal is an expertise in optimizing and creating user friendly application in Microsoft Excel & android platform for least cost ration formulation for dairy animals. His research interests include operations research, Data analytics, Mathematical modelling and statistical analysis
. He has work on these models after 8 years of experience in least cost optimization research. He is currently working as Assistant Professor of Mathematics in Faculty of Engineering & Technology, Jain (Deemed-to-be University) Bangalore. He has a total of 11 years of teaching and 8 years of researc
h experience. He has published 14 research paper in peer reviewed journals. He received many awards for his research work and has bagged the title of Best Paper Award for Least Cost Formulation for Ruminants in the International Conference on Applications of Artificial Intelligence and Computational
Mathematics (AAICM - 2020), One of his publication also received an acknowledgement of Best Paper Award on Study of Real Coded Hybrid Genetic Algorithm (RGA) to find least cost ration for non-pregnant dairy buffaloes at 7th International conference on Soft Computing for Problem Solving (SocPros-201
7) Dec 23-24 -2017 at IIT Bhubaneswar, Best paper award titled heuristic approach to nonlinear optimization technique at Research Retreat: Exploring pathways, unlocking ideas at Jain University. He is considered as the Best Mathematics Professor of the year in recognition of Continuous excellence in
teaching Awarded at International Education Awards conference 2020. He has a research collaboration with NIANP (National Institute of Animal Nutrition and Physiology) Bangalore, India. He also completed consultancy projects for ICAR-NIANP institutions and Design and Development Least Cost Feed Form
ulation (LCFF) Application for Goat, Sheep & Camel Using Excel VBA, for KING SAUD UNIVERSITY, Riyadh Saudi Arabia.Dr. Radha Gupta was born in Roorkee, Uttarakhand, in 1970. She received her M.Sc. degree in Mathematics from Agra University, Uttar Pradesh, India in 1992 and M.Phil. degree in Mathemati
cs from University of Roorkee, Uttarakhand, India, in 1993. She acquired her Ph.D. degree in Mathematics from Vikram University, Ujjain, Madhya Pradesh, India, in 2011. From 1993 to 1996, she worked as a Research Fellow with Central Building Research Institute, Roorkee, Uttarakhand. From 1999 to 200
4, she was a Lecturer in SVM PU College Bangalore; from 2004 to 2007 she was a lecturer in PES Institute of Technology, Bangalore. She moved to School of Engineering and Technology, Jain University, Bangalore, in 2007 and served the Institution as Associate Professor and Head, Department of Basic Sc
ience, till 2015. Since 2015, she has been a Professor and Head with the Mathematics department, Dayananda Sagar College of Engineering, Bangalore. Her research interests include operations research, differential equations, Mathematical modelling and statistical analysis. She is the author of five b
ooks, some conference papers and more than 50 research publications in reputed National and International journals. She is also a reviewer for some of the prestigious journals. She is a recognized Research Supervisor from VTU, Belagavi and member of many professional bodies. Dr. Radha Gupta was a re
cipient of President Gold Medal (from then President of India, Shri Shankar Dayal Sharma) for the best student of the year 1992, Agra University, Uttar Pradesh, and also a recipient of University Gold Medal for standing first class first in M.Phil. (Mathematics) in the year 1993, University of Roork
ee, Uttarakhand.Professor D. Rajendran, Principal Scientist, ICAR-National Institute of Animal Nutrition and Physiology did his Bachelor of Veterinary Science at Tamilnadu Veterinary and Animal Sciences University, Chennai in 1997 and did his Master degree in Animal Nutrition at Indian Veterinary Re
search Institute, Bareilly. He was a recipient of Junior Research Fellowship Award during his master degree. He joined as Lecturer at West Bengal University of Animal and Fishery Science in 2000. He pursued his Doctoral degree programme at Madras Veterinary College, Chennai. He received three Gold M
edal in Ph.D. namely TANUVAS Gold Medal, Dr. Richard Masilamani Memorial Award and TANUVAS Alumini Award. He joined as Assistant Professor in Animal Nutrition at Veterinary College and Research Institute, Namakkal, Taminadu and established Feed Mill under revolving fund project. He conducted researc
h on nano mineral and guided two undergraduate students to receive ALLTECH Young Scientist Award 2010 and 2011. He joined as senior scientist in 2010 at ICAR-National Institute of Animal Nutrition and Physiology, Bangalore. His pioneering work on nano technology in Animal Nutrition for improvement o
f bioavailability of mineral is eye opener for application of nano mineral science in animal nutrition. The work was recognized and received best thesis award by Animal Nutrition Journal by Elsevier Pvt. Ltd. He has 185 publications including 51 research articles, 12 book chapters, 37 technical arti
cles and 20 teaching manuals. He received 7 awards in conference and seminars of national and international repute. He was invited for a guest lecture by CG Group at Boun Me Thout, DakLak, Vietnam. He successfully guided 12 master degree and 5 doctoral degree students in the capacity of chairman/mem
ber of the advisory committee. He developed 4 software’s and 2 Android Apps and published for public use. He published 5 ready reckoners and one diagnostic kit. More than 25000 copies of the ready reckoner were sold and created revolution in the field of Animal Nutrition. He has completed successful
ly 11 externally /Institute funded research projects and currently 5 projects are undergoing. International Society of Biotechnology conferred on the Fellow of International Society of Biotechnology (FISBT) in recognition of his contribution and achievements.Dr Vishal Patil is an expertise in develo
ping and designing least cost LP & stochastic models and creating user friendly application in Microsoft Excel & android platform. He has built these models after 10 years of experience in teaching and research. He has completed consultancy projects for ICAR-NIANP institutions and Design and Develop
ment Least Cost Feed Formulation (LCFF) Application for Goat, Sheep & Camel Using Excel VBA, for KING SAUD UNIVERSITY, Riyadh Saudi Arabia. He has published 10 peer-reviewed international papers. He is working as Assistant Professor of Mathematics in Faculty of Engineering & Technology, Jain (Deemed
-to-be University) Bangalore. His major contribution includes research collaboration with NIANP (National Institute of Animal Nutrition and Physiology) Bangalore, India.
卷積神經網路結合模糊演算法應用於陰道鏡檢之 子宮頸上皮內贅瘤輔助診斷
為了解決Diagnostic algorithm 的問題，作者蔡智宇 這樣論述：
子宮頸癌為台灣女性好發性高的癌症之一，也因在演變成癌症前之病變徵兆不明顯，所以需仰賴定期抹片及陰道鏡檢查。抹片檢查結果有偽陰性之可能，故陰道鏡檢查變得十分重要，藉此及早發現癌情病變症狀並加以治療。因此運用深度學習的方法經由陰道鏡檢查影像來判斷子宮頸上皮內贅瘤的病變程度，再藉由病患身體相關的危害因子和陰道鏡檢概況來輔助診斷出病變程度。 本論文是以南部某醫學中心婦產科的陰道鏡檢查圖像為研究數據，並利用卷積神經網路將陰道鏡檢影像進行特徵擷取之訓練與學習，再透過指定病例影像對其組織變化概況評比相似程度，最後將相似程度和病患身體數據透過模糊演算法評估強化其子宮頸上皮內增生分級判定評估。
本研究將陰道鏡圖分別依輕度子宮頸異常增生、中度子宮頸異常增生及子宮頸原位癌三類為訓練數據，並隨機抓取三類中的陰道鏡影像為測試數據。根據實驗結果顯示子宮頸上皮內贅瘤的驗證準確率約達85.38%，透過卷積神經網路模型的病徵分級預估分析，結合病患身體數據強化預測病變程度，協助醫師避免主觀經驗判斷，也提供給經驗不足的醫生作為診斷參考，以達到輔助診斷，給予病患最適合的處置方式。
Biomarker Analysis in Clinical Trials with R
為了解決Diagnostic algorithm 的問題，作者Rabbee, Nusrat 這樣論述：
Nusrat Rabbee is a biostatistician and data scientist at Rabbee & Associates, where she creates innovative solutions to help companies accelerate drug and diagnostic development for patients. Her research interest lies in the intersection of data science and personalized medicine. She has extensive
experience in bioinformatics, clinical statistics and high-dimensional data analyses. She has co-discovered the RLMM algorithm for genotyping Affymetrix SNP chips and co-invented a high-dimensional molecular signature for cancer. She has spent over 17 years in the pharmaceutical and diagnostics indu
stry focusing on biomarker development. She has taught statistics at UC Berkeley for 4 years.
級聯 YOLO 與巢狀 U 型卷積神經網路之超參數優化於腦脊髓液磁振影像切割
為了解決Diagnostic algorithm 的問題，作者丁俞文 這樣論述：
在自發性顱內低壓臨床醫學中，已有文獻證實透過定性或定量的方式評估此疾病，且此疾病具有即時診斷之重要性及必要性，而使用非侵入式診斷磁振造影(MRI)作為初步診斷之工具，若醫師使用定性的方式觀察影像，則需要耗費相當多時間且可能造成醫療人員疲勞造成判斷錯誤，結果易受主觀感受影響。過去已有文獻指出病患恢復情形與腦脊髓液容積相關，可透過量化方式計算腦脊髓液容積，提供更客觀的診斷方式，因此如何準確地分割腦脊髓液為重要議題。因此本研究使用深度學習的巢狀U型卷積神經網路分割出腦脊髓液分佈區域，並使用YOLO圈選出關注區域範圍。最後將預測之影像進行二值化後輸出，進行後續量化研究及績效衡量。脊髓區域之腦脊髓液磁
振造影資料來源由台中榮民總醫院提供，共25為樣本(25603張影像)。脊髓區域之影像使用U-Net結合網格搜索及YOLOv4取得IoU為0.9399、DSC為0.9690；巢狀U型卷積神經網路結合網格搜索及YOLOv4 IoU為0.9398、DSC為0.9690，其中U-Net網格搜索的最佳參數組合為學習率(Learning rate)：0.00001、Batch size：7、Epoch：200；巢狀U型卷積神經網路結合網格搜索的最佳參數組合為學習率(Learning rate)：0.00001、Batch size：7、Epoch：200。最後量化腦脊髓液容積與黃金標準之誤差為0.33%~
16.28%與0.51%~15.71%。