AIMC Topic: Socioeconomic Factors
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Measuring social, environmental and health inequalities using deep learning and street imagery.
Scientific reports
Apr 18, 2019
Cities are home to an increasing majority of the world's population. Currently, it is difficult to track social, economic, environmental and health outcomes in cities with high spatial and temporal resolution, needed to evaluate policies regarding ur...
A Comparative Texture Analysis Based on NECT and CECT Images to Differentiate Lung Adenocarcinoma from Squamous Cell Carcinoma.
Journal of medical systems
Feb 1, 2019
The purpose of the study was to compare the texture based discriminative performances between non-contrast enhanced computed tomography (NECT) and contrast-enhanced computed tomography (CECT) images in differentiating lung adenocarcinoma (ADC) from s...
Machine Learning to Predict Delays in Adjuvant Radiation following Surgery for Head and Neck Cancer.
Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
Jan 29, 2019
OBJECTIVE: To apply a novel methodology with machine learning (ML) to a large national cancer registry to help identify patients who are high risk for delayed adjuvant radiation.
Machine Learning Can Improve Estimation of Surgical Case Duration: A Pilot Study.
Journal of medical systems
Jan 17, 2019
Operating room (OR) utilization is a significant determinant of hospital profitability. One aspect of this is surgical scheduling, which depends on accurate predictions of case duration. This has been done historically by either the surgeon based on ...
Time-lagged effects of weekly climatic and socio-economic factors on ANN municipal yard waste prediction models.
Waste management (New York, N.Y.)
Nov 27, 2018
Efficient and effective solid waste management requires sufficient ability to predict the operational capacity of a system correctly. Waste prediction models have been widely studied and these models are always being challenged to perform more accura...
High rates of atherogenic dyslipidemia, β-cell function loss, and microangiopathy among Turkish migrants with T2DM.
Diabetes & metabolic syndrome
Nov 24, 2018
AIMS: Non-Caucasian migrants require dedicated approaches in diabetes management due to specific genetic; socio-cultural; demographic and anthropological determinants. Documenting such phenotypes allows for better understanding unmet needs and manage...
Predicting the risk of emergency admission with machine learning: Development and validation using linked electronic health records.
PLoS medicine
Nov 20, 2018
BACKGROUND: Emergency admissions are a major source of healthcare spending. We aimed to derive, validate, and compare conventional and machine learning models for prediction of the first emergency admission. Machine learning methods are capable of ca...
Risk Factors
Aged
Aged, 80 and over
Young Adult
Middle Aged
Risk Assessment
England
Adult
Male
Machine Learning
Electronic Health Records
Female
Reproducibility of Results
Humans
Patient Admission
Needs Assessment
Age Factors
Emergency Service, Hospital
Data Mining
Sex Factors
Health Services Needs and Demand
Adolescent
Time Factors
Socioeconomic Factors
Health Status
Multiple Human-Behaviour Indicators for Predicting Lung Cancer Mortality with Support Vector Machine.
Scientific reports
Nov 9, 2018
Lung cancer is still one of the most common causes of death around the world, while there is overwhelming evidence that the environment and lifestyle factors are predominant causes of most sporadic cancers. However, when applying human-behaviour indi...
A neurodynamic approach to nonlinear optimization problems with affine equality and convex inequality constraints.
Neural networks : the official journal of the International Neural Network Society
Oct 28, 2018
This paper presents a neurodynamic approach to nonlinear optimization problems with affine equality and convex inequality constraints. The proposed neural network endows with a time-varying auxiliary function, which can guarantee that the state of th...
Predictive models for charitable giving using machine learning techniques.
PloS one
Oct 3, 2018
Private giving represents more than three fourths of all U.S. charitable donations, about 2% of total Gross Domestic Product (GDP). Private giving is a significant factor in funding the nonprofit sector of the U.S. economy, which accounts for more th...
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