AIMC Topic: Prospective Studies

Clear Filters Showing 1561 to 1570 of 2510 articles

Visual Speech Recognition: Improving Speech Perception in Noise through Artificial Intelligence.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVES: To compare speech perception (SP) in noise for normal-hearing (NH) individuals and individuals with hearing loss (IWHL) and to demonstrate improvements in SP with use of a visual speech recognition program (VSRP).

Can Building "Artificially Intelligent Cities" Safeguard Humanity from Natural Disasters, Pandemics, and Other Catastrophes? An Urban Scholar's Perspective.

Sensors (Basel, Switzerland)
In recent years, artificial intelligence (AI) has started to manifest itself at an unprecedented pace. With highly sophisticated capabilities, AI has the potential to dramatically change our cities and societies. Despite its growing importance, the u...

The development an artificial intelligence algorithm for early sepsis diagnosis in the intensive care unit.

International journal of medical informatics
BACKGROUND: Severe sepsis and septic shock are still the leading causes of death in Intensive Care Units (ICUs), and timely diagnosis is crucial for treatment outcomes. The progression of electronic medical records (EMR) offers the possibility of sto...

Resting-State Brain Activity for Early Prediction Outcome in Postanoxic Patients in a Coma with Indeterminate Clinical Prognosis.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Early outcome prediction of postanoxic patients in a coma after cardiac arrest proves challenging. Current prognostication relies on multimodal testing, using clinical examination, electrophysiologic testing, biomarkers, and s...

Machine learning provides evidence that stroke risk is not linear: The non-linear Framingham stroke risk score.

PloS one
Current stroke risk assessment tools presume the impact of risk factors is linear and cumulative. However, both novel risk factors and their interplay influencing stroke incidence are difficult to reveal using traditional additive models. The goal of...

Using machine learning to improve our understanding of injury risk and prediction in elite male youth football players.

Journal of science and medicine in sport
OBJECTIVES: The purpose of this study was to examine whether the use of machine learning improved the ability of a neuromuscular screen to identify injury risk factors in elite male youth football players.