Medical 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

Can We Trust Ai?

為了解決Medical algorithm的問題，作者Chellappa, Rama 這樣論述：

Artificial intelligence is part of our daily lives. How can we address its limitations and guide its use for the benefit of communities worldwide?Artificial intelligence (AI) has evolved from an experimental computer algorithm used by academic researchers to a commercially reliable method of sift

ing through large sets of data that detect patterns not readily apparent through more rudimentary search tools. As a result, AI-based programs are helping doctors make more informed decisions about patient care, city planners align roads and highways to reduce traffic congestion with better efficien

cy, and merchants scan financial transactions to quickly flag suspicious purchases. But as AI applications grow, concerns have increased, too, including worries about applications that amplify existing biases in business practices and about the safety of self-driving vehicles. In Can We Trust AI?, D

r. Rama Chellappa, a researcher and innovator with 40 years in the field, recounts the evolution of AI, its current uses, and how it will drive industries and shape lives in the future. Leading AI researchers, thought leaders, and entrepreneurs contribute their expertise as well on how AI works, wha

t we can expect from it, and how it can be harnessed to make our lives not only safer and more convenient but also more equitable. Can We Trust AI? is essential reading for anyone who wants to understand the potential--and pitfalls--of artificial intelligence. The book features: - an exploration of

AI’s origins during the post-World War II era through the computer revolution of the 1960s and 1970s, and its explosion among technology firms since 2012;- highlights of innovative ways that AI can diagnose medical conditions more quickly and accurately;- explanations of how the combination of AI an

d robotics is changing how we drive; and- interviews with leading AI researchers who are pushing the boundaries of AI for the world’s benefit and working to make its applications safer and more just. Johns Hopkins WavelengthsIn classrooms, field stations, and laboratories in Baltimore and around the

world, the Bloomberg Distinguished Professors of Johns Hopkins University are opening the boundaries of our understanding of many of the world’s most complex challenges. The Johns Hopkins Wavelengths book series brings readers inside their stories, illustrating how their pioneering discoveries and

innovations benefit people in their neighborhoods and across the globe in artificial intelligence, cancer research, food systems’ environmental impacts, health equity, planetary science, science diplomacy, and other critical arenas of study. Through these compelling narratives, their insights will s

park conversations from dorm rooms to dining rooms to boardrooms.

Medical algorithm進入發燒排行的影片

基於PPG信號和卷積神經網路測量血壓

為了解決Medical algorithm的問題，作者黎文雄 這樣論述：

光體積變化描記圖法 (PPG) 是一種非侵入性和低成本的技術，現在被廣泛應用於許多血壓量測的研究中。儘管 PPG 信號的品質對血壓演算法的準確度有很大影響，但有關PPG信號的品質檢查並未得到重點關注。在實際量測時，除PPG信號外，反相PPG信號、雜訊、運動信號都會被採集，這些錯誤的信號如果無法去除就會導致錯誤的預測結果。因此，為了解決這個問題，本文提出了一種用於檢查PPG信號品質的新型卷積神經網路 (CNN) 模型，此使用新型CNN的品質檢查模型已被成功訓練和驗證，具有高精度和高性能。此外，本文還設計了另一個卷積神經網路模型來計算血壓，該模型可以自動檢測 PPG 信號中的重要特徵。最後，品質

檢查模型和 CNN 模型都成功嵌入到 Matlab 界面中，用於測量和收集更多數據，以便將來校準模型。

Illumination of Artificial Intelligence in Cybersecurity and Forensics

為了解決Medical algorithm的問題，作者 這樣論述：

A Practical Experience Applying Security Audit Techniques in an Industrial Healthcare System.- Feature Extraction and Artificial Intelligence-Based Intrusion Detection Model for a Secure Internet of Things Networks.- Intrusion Detection using Anomaly Detection Algorithm and Snort.- Research Perspect

ive on Digital Forensic Tools and Investigation Process.- Intelligent Authentication Framework for Internet of Medical Things (IoMT).- Parallel Faces Recognition Attendance System with Anti-spoofing using Convolutional Neural Network.- A Systematic Literature Review on Face Morphing Attack Detection

(MAD).- Averaging Dimensionality Reduction and Feature Level Fusion for Post-Processed Morphed Face Image Attack Detection.- A Systematic Literature Review on Forensics in Cloud, IoT, AI & Blockchain.- Predictive Forensic Based - Characterization of Hidden Elements in Criminal Networks using Baum-W

elch Optimization Technique.- An Integrated IDS using ICA-based Feature Selection and SVM Classification Method.- A Binary Firefly Algorithm Based Feature Selection Method on High Dimensional Intrusion Detection Data.- Graphical Based Authentication Method Combined with City Block Distance for Elect

ronic Payment System.- Authenticated Encryption to Prevent Cyberattacks in images.- Machine Learning in Automated Detection of Ransomware: Scope, Benefits and Challenges.

設計與實作應用於西瓜採集無人機系統之人工智慧電腦視覺系統

為了解決Medical algorithm的問題，作者馬約瑟 這樣論述：

本文設計和實現了一種用於採集、導航和檢測西瓜的計算機視覺系統的,該系統使用無人駕駛飛機且無需人工干預。該系統實現了單板計算機Nvidia Jetson Nano和為圖像傳輸樣式(Pix2Pix)而創建的捲積神經網絡。這些元素整合在一起用於檢測,姿態估計和導航以達到目標。所有流程均由狀態機管理,該狀態機負責激活或停用在後台運行的不同流程步驟。ROS平台用於創建不同進程之間的數據交換。無人機使用稱為mavlink的標準化協議來將單板計算機與飛行計算機進行通信。ROS環境中的mavros用於解釋兩個元素之間的所有數據。無人機的目標是創建一個無監督的系統以快速便捷的方式處理繁重的任務,例如西瓜收穫。

用於檢測的神經網絡結構經設計可達到30幀FPS,可在配套計算機中滿足較高的可靠性,較低的內存使用以及快速判斷來滿足這三個條件,這些條件對於實現自主飛行是必不可少的。