AIMC Topic: Machine Learning

Clear Filters Showing 6681 to 6690 of 34417 articles

Raising awareness may increase the likelihood of hematopoietic stem cell donation: a nationwide survey using artificial intelligence.

International journal of hematology
BACKGROUND: In Italy, the demand for allogeneic transplantation exceeds the number of compatible donors in the Italian Bone Marrow Donor Registry (IBMDR). This study aimed to explore the knowledge, beliefs, opinions, values, and feelings of the Itali...

Towards A universal settling model for microplastics with diverse shapes: Machine learning breaking morphological barriers.

Water research
Accurately predicting the settling velocity of microplastics in aquatic environments is a prerequisite for reliably modeling their transport processes. An increasing number of settling models have been proposed for microplastics with fragmented, film...

ARTIFICIAL INTELLIGENCE PLATFORMS IN DENTAL CARIES DETECTION: A SYSTEMATIC REVIEW AND META-ANALYSIS.

The journal of evidence-based dental practice
OBJECTIVES: To assess Artificial Intelligence (AI) platforms, machine learning methodologies and associated accuracies used in detecting dental caries from clinical images and dental radiographs.

Machine learning-assisted implantable plant electrophysiology microneedle sensor for plant stress monitoring.

Biosensors & bioelectronics
Plant electrical signals serve as a medium for long-distance signal transmission and are intricately linked to plant stress responses. High-fidelity acquisition and analysis of plant electrophysiological signals contribute to early stress identificat...

Firearm Injury Risk Prediction Among Children Transported by 9-1-1 Emergency Medical Services: A Machine Learning Analysis.

Pediatric emergency care
OBJECTIVE: Among children transported by ambulance across the United States, we used machine learning models to develop a risk prediction tool for firearm injury using basic demographic information and home ZIP code matched to publicly available data...

Time-Frequency functional connectivity alterations in Alzheimer's disease and frontotemporal dementia: An EEG analysis using machine learning.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Alzheimer's disease (AD) and frontotemporal dementia (FTD) are prevalent neurodegenerative diseases characterized by altered brain functional connectivity (FC), affecting over 100 million people worldwide. This study aims to identify disti...

Glaucoma detection: Binocular approach and clinical data in machine learning.

Artificial intelligence in medicine
In this work, we present a multi-modal machine learning method to automate early glaucoma diagnosis. The proposed methodology introduces two novel aspects for automated diagnosis not previously explored in the literature: simultaneous use of ocular f...

Blood Biomarker Signatures for Slow Gait Speed in Older Adults: An Explainable Machine Learning Approach.

Brain, behavior, and immunity
Maintaining physical function is crucial for independent living in older adults, with gait speed being a key predictor of health outcomes. Blood biomarkers may potentially monitor older adults' mobility, yet their association with slow gait speed sti...

Prediction of stroke-associated hospital-acquired pneumonia: Machine learning approach.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: Stroke-associated Hospital Acquired Pneumonia (HAP) significantly impacts patient outcomes. This study explores the utility of machine learning models in predicting HAP in stroke patients, leveraging national registry data and SHapley Add...

Smartphone pupillometry with machine learning differentiates ischemic from hemorrhagic stroke: A pilot study.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: Similarities between acute ischemic and hemorrhagic stroke make diagnosis and triage challenging. We studied a smartphone-based quantitative pupillometer for differentiation of acute ischemic and hemorrhagic stroke.