AIMC Topic: Humans

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Radiography students' perceptions of artificial intelligence in medical imaging.

Journal of medical imaging and radiation sciences
INTRODUCTION: Education relating to Artificial Intelligence (AI) is becoming critical to developing contemporary radiographers. This study sought to investigate the perceptions of a sample of Australian radiography students regarding AI within the co...

Deep Learning for Perfusion Cerebral Blood Flow (CBF) and Volume (CBV) Predictions and Diagnostics.

Annals of biomedical engineering
Dynamic susceptibility contrast magnetic resonance perfusion (DSC-MRP) is a non-invasive imaging technique for hemodynamic measurements. Various perfusion parameters, such as cerebral blood volume (CBV) and cerebral blood flow (CBF), can be derived f...

Information fusion for infant age estimation from deciduous teeth using machine learning.

American journal of biological anthropology
OBJECTIVES: Over the past few years, several methods have been proposed to improve the accuracy of age estimation in infants with a focus on dental development as a reliable marker. However, traditional approaches have limitations in efficiently comb...

Deep Learning Prediction of Cervical Spine Surgery Revision Outcomes Using Standard Laboratory and Operative Variables.

World neurosurgery
BACKGROUND: Cervical spine procedures represent a major proportion of all spine surgery. Mitigating the revision rate following cervical procedures requires careful patient selection. While complication risk has successfully been predicted, revision ...

Deep match: A zero-shot framework for improved fiducial-free respiratory motion tracking.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Motion management is essential to reduce normal tissue exposure and maintain adequate tumor dose in lung stereotactic body radiation therapy (SBRT). Lung SBRT using an articulated robotic arm allows dynamic tracking during rad...

Predicting Soccer Players' Fitness Status Through a Machine-Learning Approach.

International journal of sports physiology and performance
PURPOSE: The study had 3 purposes: (1) to develop an index using machine-learning techniques to predict the fitness status of soccer players, (2) to explore the index's validity and its relationship with a submaximal run test (SMFT), and (3) to analy...

Machine learning algorithms to predict outcomes in children and adolescents with COVID-19: A systematic review.

Artificial intelligence in medicine
BACKGROUND AND OBJECTIVES: We aimed to analyze the study designs, modeling approaches, and performance evaluation metrics in studies using machine learning techniques to develop clinical prediction models for children and adolescents with COVID-19.