Modelling Environmental Impact on Public Health using Machine Learning: Case Study on Asthma

2020 ◽  
Author(s):  
Lakmini Wijesekara ◽  
Liwan Liyanage
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Environmental Impact

scholarly journals Machine Learning for Neonatal Mortality Risk Assessment: A Case Study Using Public Health Data from São Paulo

2020 ◽  
Author(s):  
Carlos Eduardo Beluzo ◽  
Luciana Correia Alves ◽  
Rodrigo Bresan ◽  
Natália Arruda ◽  
Ricardo Sovat ◽  
...  
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Risk Assessment ◽  
Network Architecture ◽  
Health Data ◽  
Sao Paulo ◽  
São Paulo ◽  
Public Health Data ◽  
Tools And Techniques

AbstractInfant mortality is a reflection of a complex combination of biological, socioeconomic and health care factors that require various data sources for a thorough analysis. Consequently, the use of specialized tools and techniques to deal with a large volume of data is extremely helpful. Machine learning has been applied to solve problems from many domains and presents great potential for the proposed problem, which would be an innovation in Brazilian reality. In this paper, an innovative method is proposed to perform a neonatal death risk assessment using computer vision techniques. Using mother, pregnancy care and child at birth features, from a dataset containing neonatal samples from São Paulo city public health data, the proposed method encodes images features and uses a custom convolutional neural network architecture to classification. Experiments show that the method is able to detect death samples with accuracy of 90.61%.

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.

Identifying Public Health Problems

2018 ◽  
Author(s):  
Scott Burris ◽  
Micah L. Berman ◽  
Matthew Penn, and ◽  
Tara Ramanathan Holiday
Keyword(s):  
Public Health ◽  
Health Problems ◽  
Health Priorities ◽  
Disability Adjusted Life Years ◽  
Quality Adjusted Life Years ◽  
Disability Adjusted Life ◽  
Life Years ◽  
Study Designs ◽  
Quality Adjusted Life

Chapter 5 discusses the use of epidemiology to identify the source of public health problems and inform policymaking. It uses a case study to illustrate how researchers, policymakers, and practitioners detect diseases, identify their sources, determine the extent of an outbreak, and prevent new infections. The chapter also defines key measures in epidemiology that can indicate public health priorities, including morbidity and mortality, years of potential life lost, and measures of lifetime impacts, including disability-adjusted life years and quality-adjusted life years. Finally, the chapter reviews epidemiological study designs, differentiating between experimental and observational studies, to show how to interpret data and identify limitations.

Paper2Wire – A Case Study of User-Centred Development of Machine Learning Tools for UX Designers

i-com ◽  
2021 ◽  
Vol 20 (1) ◽  
pp. 19-32
Author(s):  
Daniel Buschek ◽  
Charlotte Anlauff ◽  
Florian Lachner
Keyword(s):  
Machine Learning ◽  
Development Process ◽  
User Study ◽  
Concept Development ◽  
Lessons Learned ◽  
Design Tool ◽  
Learning Tools ◽  
Interface Elements ◽  
Industry Partner

Abstract This paper reflects on a case study of a user-centred concept development process for a Machine Learning (ML) based design tool, conducted at an industry partner. The resulting concept uses ML to match graphical user interface elements in sketches on paper to their digital counterparts to create consistent wireframes. A user study (N=20) with a working prototype shows that this concept is preferred by designers, compared to the previous manual procedure. Reflecting on our process and findings we discuss lessons learned for developing ML tools that respect practitioners’ needs and practices.

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