AIMC Topic: Humans

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WFUMB Commentary Paper on Artificial intelligence in Medical Ultrasound Imaging.

Ultrasound in medicine & biology
Artificial intelligence (AI) is defined as the theory and development of computer systems able to perform tasks normally associated with human intelligence. At present, AI has been widely used in a variety of ultrasound tasks, including in point-of-c...

People expect artificial moral advisors to be more utilitarian and distrust utilitarian moral advisors.

Cognition
As machines powered by artificial intelligence increase in their technological capacities, there is a growing interest in the theoretical and practical idea of artificial moral advisors (AMAs): systems powered by artificial intelligence that are expl...

Prospective Evaluation of Real-Time Artificial Intelligence for the Hill Classification of the Gastroesophageal Junction.

United European gastroenterology journal
BACKGROUND: Assessment of the gastroesophageal junction (GEJ) is an integral part of gastroscopy; however, the absence of standardized reporting hinders consistency of examination documentation. The Hill classification offers a standardized approach ...

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...

ItpCtrl-AI: End-to-end interpretable and controllable artificial intelligence by modeling radiologists' intentions.

Artificial intelligence in medicine
Using Deep Learning in computer-aided diagnosis systems has been of great interest due to its impressive performance in the general domain and medical domain. However, a notable challenge is the lack of explainability of many advanced models, which p...

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.