Comparative Study of Principle and Independent Component Analysis of CNN for Embryo Stage and Fertility Classification

Abstract

background: Applications of deep learning for the societal issues are one of the debatable concerns where the community medicine and implication of artificial intelligence for the societal issues are a big concern. This article, it is shown the applications of neural networks in clinical practice for reproduction procedure enhancement. And this is a well-known issue where image analysis has the exact applications. In Embryology, fetal abnormality early-stage detection and diagnosis is one of the challenging tasks and thus, needs automation in the process of tomography and ultrasonic imaging. Also, Interpretation and accuracy in the medical imaging process are very important for accurate results.

Semi-Supervised Clustering-Based DANA Algorithm for Data Gathering and Disease Detection in Healthcare Wireless Sensor Networks (WSN)

“…In this table, the correlation hypothesis across different algorithms is analyzed over time (T1-T5) and across various clusters (K1-K8). The 'Distance Measures' columns (1)(2)(3)(4) represent the distances between the nodes within each cluster. 'Fuzzy','Leach','K-Mean', and 'DANA' columns represent the correlation values or probabilities associated with each cluster for the respective algorithms.…”

“…Innovative applications, such as signal processing-based disease diagnosis, have been made possible by their capacity to monitor patients’ physiological data in real-time and non-invasively. In order to enhance patient outcomes and enable prompt action, early and accurate disease diagnosis is essential in healthcare [ 4 ]. Deploying WSNs in healthcare environments, however, poses special difficulties.…”