AI Medical Compendium Topic

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Using machine learning to examine street green space types at a high spatial resolution: Application in Los Angeles County on socioeconomic disparities in exposure.

The Science of the total environment
BACKGROUND: Compared to commonly-used green space indicators from downward-facing satellite imagery, street view-based green space may capture different types of green space and represent how environments are perceived and experienced by people on th...

A comparative study on image-based snake identification using machine learning.

Scientific reports
Automated snake image identification is important from different points of view, most importantly, snake bite management. Auto-identification of snake images might help the avoidance of venomous snakes and also providing better treatment for patients...

Assessing Inequity in Green Space Exposure toward a "15-Minute City" in Zhengzhou, China: Using Deep Learning and Urban Big Data.

International journal of environmental research and public health
Green space exposure is considered an important aspect of a livable environment and human well-being. It is often regarded as an indicator of social justice. However, due to the difficulties in obtaining green space exposure data from a ground-based ...

Artificial Intelligence and Public Health: An Exploratory Study.

International journal of environmental research and public health
Artificial intelligence (AI) has the potential to revolutionize research by automating data analysis, generating new insights, and supporting the discovery of new knowledge. The top 10 contribution areas of AI towards public health were gathered in t...

Prediction of essential oil content in C. sintoc Leaves based on the direction of vegetation slope in Mount Ciremai National Park using ANFIS Artificial Neural Network.

Brazilian journal of biology = Revista brasleira de biologia
C. sintoc is a plant that has a high essential oil content. Essential oils have many health benefits. Mount Ciremai National Park is an area that has abundant vegetation, especially C. sintoc. The purpose of this study was to predict the volume of oi...

An integrated passive acoustic monitoring and deep learning pipeline for black-and-white ruffed lemurs (Varecia variegata) in Ranomafana National Park, Madagascar.

American journal of primatology
The urgent need for effective wildlife monitoring solutions in the face of global biodiversity loss has resulted in the emergence of conservation technologies such as passive acoustic monitoring (PAM). While PAM has been extensively used for marine m...

Assessing greenspace and cardiovascular health through deep-learning analysis of street-view imagery in a cohort of US children.

Environmental research
BACKGROUND: Accurately capturing individuals' experiences with greenspace at ground-level can provide valuable insights into their impact on children's health. However, most previous research has relied on coarse satellite-based measurements.

Modeling land use and land cover dynamics of Bale Mountains National Park using Google Earth Engine and cellular automata-artificial neural network (CA-ANN) model.

PloS one
This research aimed to assess the observed land use and land cover (LULC) changes of Bale Mountains National Park (BMNP) from 1993 to 2023 and its future projections for the years (2033 and 2053). The study utilized multi-date Landsat imagery from 19...

Optimization of urban green space in Wuhan based on machine learning algorithm from the perspective of healthy city.

Frontiers in public health
INTRODUCTION: Urban green spaces play a critical role in addressing health issues, ecological challenges, and uneven resource distribution in cities. This study focuses on Wuhan, where low green coverage rates and imbalanced green space allocation po...

Heavy metals prediction system in groundwater using online sensor and machine learning for water management: the case of typical industrial park.

Environmental pollution (Barking, Essex : 1987)
With the expansion of human industrial activities, heavy metal contamination in groundwater environments has become increasingly severe. Environmental management agencies invest significant financial resources into groundwater monitoring, primarily d...