AIMC Topic: Machine Learning

Clear Filters Showing 11831 to 11840 of 34417 articles

Discovering Subgroups of Children With High Mortality in Urban Guinea-Bissau: Exploratory and Validation Cohort Study.

JMIR public health and surveillance
BACKGROUND: The decline in global child mortality is an important public health achievement, yet child mortality remains disproportionally high in many low-income countries like Guinea-Bissau. The persisting high mortality rates necessitate targeted ...

Assessment of rainfall-derived inflow and infiltration in sewer systems with machine learning approaches.

Water science and technology : a journal of the International Association on Water Pollution Research
Rainfall-derived inflow/infiltration (RDII) modelling during heavy rainfall events is essential for sewer flow management. In this study, two machine learning algorithms, random forest (RF) and long short-term memory (LSTM), were developed for sewer ...

Game-theoretic optimization of landslide susceptibility mapping: a comparative study between Bayesian-optimized basic neural network and new generation neural network models.

Environmental science and pollution research international
Landslide susceptibility mapping is essential for reducing the risk of landslides and ensuring the safety of people and infrastructure in landslide-prone areas. However, little research has been done on the development of well-optimized Elman neural ...

Prioritization of genes for translation: a computational approach.

Expert review of proteomics
INTRODUCTION: Gene identification for genetic diseases is critical for the development of new diagnostic approaches and personalized treatment options. Prioritization of gene translation is an important consideration in the molecular biology field, a...

Validation of Machine Learning-Based Assessment of Major Depressive Disorder from Paralinguistic Speech Characteristics in Routine Care.

Depression and anxiety
New developments in machine learning-based analysis of speech can be hypothesized to facilitate the long-term monitoring of major depressive disorder (MDD) during and after treatment. To test this hypothesis, we collected 550 speech samples from tele...

Debris flow volume prediction model based on back propagation neural network optimized by improved whale optimization algorithm.

PloS one
Debris flow is a sudden natural disaster in mountainous areas, which seriously threatens the lives and property of nearby residents. Therefore, it is necessary to predict the volume of debris flow accurately and reliably. However, the predictions of ...

Improving traffic accident severity prediction using MobileNet transfer learning model and SHAP XAI technique.

PloS one
Traffic accidents remain a leading cause of fatalities, injuries, and significant disruptions on highways. Comprehending the contributing factors to these occurrences is paramount in enhancing safety on road networks. Recent studies have demonstrated...

Late Life Cognitive Function Trajectory Among the Chinese Oldest-Old Population-A Machine Learning Approach.

Journal of gerontological social work
Informed by the biopsychosocial framework, our study uses the Chinese Longitudinal Healthy Longevity Survey (CLHLS) dataset to examine cognitive function trajectories among the oldest-old (80+). Employing K-means clustering, we identified two latent ...

An artificial intelligence-driven scoring system to measure histological disease activity in ulcerative colitis.

United European gastroenterology journal
BACKGROUND AND AIMS: Assessment and scoring of histological images in Ulcerative colitis (UC) is prone to inter- and intra-observer variability. This study aimed to investigate whether an artificial intelligence (AI) system developed using image proc...

Detecting inattentive respondents by machine learning: A generic technique that substitutes for the directed questions scale and compensates for its shortcomings.

Behavior research methods
Web surveys are often used to collect data for psychological research. However, the inclusion of many inattentive respondents can be a problem. Various methods for detecting inattentive respondents have been proposed, most of which require the inclus...