Death Rate

Death rate research focuses on understanding and predicting mortality across populations, driven by the need to improve public health interventions and resource allocation. Current investigations utilize machine learning, including convolutional neural networks, to analyze diverse factors influencing mortality, such as dietary habits and the timely diagnosis of diseases like pneumonia. These studies highlight disparities in healthcare access and outcomes, particularly in underdeveloped regions, underscoring the importance of developing accessible and accurate diagnostic tools. Ultimately, improved understanding of death rate determinants through data-driven approaches can lead to more effective disease prevention and management strategies globally.

Papers

February 19, 2024

Evaluation of Country Dietary Habits Using Machine Learning Techniques in Relation to Deaths from COVID-19
María Teresa García-Ordás, Natalia Arias, Carmen Benavides, Oscar García-Olalla, José Alberto Benítez-Andrades
Machine Learning Global Evaluation Covid 19 Cereal Grain Death Rate

October 10, 2022

Using Deep Learning to Improve Early Diagnosis of Pneumonia in Underdeveloped Countries
Kyler Larsen
Deep Learning Ventilator Associated Pneumonia Early Diagnosis Death Rate

Death Rate

Papers

Evaluation of Country Dietary Habits Using Machine Learning Techniques in Relation to Deaths from COVID-19

Using Deep Learning to Improve Early Diagnosis of Pneumonia in Underdeveloped Countries