scholarly journals Research of Machine Learning Algorithm for Broadcasting Spectrum Signal Processing

2019 ◽  
Vol 569 ◽  
pp. 052083
Author(s):  
Jinyu Sun ◽  
Qun Zhou ◽  
Jianping Shang ◽  
Shuai Sun
Keyword(s):  
Machine Learning ◽  
Signal Processing ◽  
Learning Algorithm ◽  
Machine Learning Algorithm

Signal Processing and Machine‐learning Algorithm to classify anesthesia depth

2020 ◽  
Vol 34 (S1) ◽  
pp. 1-1
Author(s):  
Dario Reyes-Cruz ◽  
Oscar Leonardo Mosquera ◽  
Daniel Alfonso Botero-Rosas ◽  
John Jairo Gallego-Correa ◽  
Henry H. Leon-Ariza ◽  
...  
Keyword(s):  
Machine Learning ◽  
Signal Processing ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Anesthesia Depth

Signal Processing and Pattern Recognition in Electronic Tongues

2020 ◽  
pp. 84-108
Author(s):  
Jersson X. Leon-Medina ◽  
Maribel Anaya Vejar ◽  
Diego A. Tibaduiza
Keyword(s):  
Machine Learning ◽  
Pattern Recognition ◽  
Signal Processing ◽  
Learning Algorithm ◽  
Electronic Tongue ◽  
Sensor Arrays ◽  
Practical Implementation ◽  
Machine Learning Algorithm ◽  
Use Of Data ◽  
Processing Strategies

This chapter reviews the development of solutions related to the practical implementation of electronic tongue sensor arrays. Some of these solutions are associated with the use of data from different instrumentation and acquisition systems, which may vary depending on the type of data collected, the use and development of data pre-processing strategies, and their subsequent analysis through the development of pattern recognition methodologies. Most of the time, these methodologies for signal processing are composed of stages for feature selection, feature extraction, and finally, classification or regression through a machine learning algorithm.

Machine Learning Algorithm to Predict Early Complications after Brain Tumor Surgery

2018 ◽  
Author(s):  
C.H.B. van Niftrik ◽  
F. van der Wouden ◽  
V. Staartjes ◽  
J. Fierstra ◽  
M. Stienen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Brain Tumor ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Tumor Surgery ◽  
Early Complications ◽  
Brain Tumor Surgery

Feature extraction and prediction of Dengue Outbreaks

2020 ◽  
pp. 216-222
Author(s):  
Kunal Parikh ◽  
Tanvi Makadia ◽  
Harshil Patel
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Developing Countries ◽  
Feature Extraction ◽  
Predictive Analytics ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Health Concerns ◽  
The World ◽  
Dengue Outbreaks

Dengue is unquestionably one of the biggest health concerns in India and for many other developing countries. Unfortunately, many people have lost their lives because of it. Every year, approximately 390 million dengue infections occur around the world among which 500,000 people are seriously infected and 25,000 people have died annually. Many factors could cause dengue such as temperature, humidity, precipitation, inadequate public health, and many others. In this paper, we are proposing a method to perform predictive analytics on dengue’s dataset using KNN: a machine-learning algorithm. This analysis would help in the prediction of future cases and we could save the lives of many.

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