AIMC Topic: Humans

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Extracting diffusion tensor fractional anisotropy and mean diffusivity from 3-direction DWI scans using deep learning.

Magnetic resonance in medicine
PURPOSE: To develop and evaluate machine-learning methods that reconstruct fractional anisotropy (FA) values and mean diffusivities (MD) from 3-direction diffusion MRI (dMRI) acquisitions.

Applications of Artificial Intelligence in Musculoskeletal Imaging: From the Request to the Report.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Artificial intelligence (AI) will transform every step in the imaging value chain, including interpretive and noninterpretive components. Radiologists should familiarize themselves with AI developments to become leaders in their clinical implementati...

Using Machine Learning to Make Predictions in Patients Who Fall.

The Journal of surgical research
BACKGROUND: As the population ages, the incidence of traumatic falls has been increasing. We hypothesize that a machine learning algorithm can more accurately predict mortality after a fall compared with a standard logistic regression (LR) model base...

Machine learning-based mortality rate prediction using optimized hyper-parameter.

Computer methods and programs in biomedicine
OBJECTIVE AND BACKGROUND: The current scenario of the Pandemic of COVID-19 demands multi-channel investigations and predictions. A variety of prediction models are available in the literature. The majority of these models are based on extrapolating b...

High tissue contrast image synthesis via multistage attention-GAN: Application to segmenting brain MR scans.

Neural networks : the official journal of the International Neural Network Society
Magnetic resonance imaging (MRI) presents a detailed image of the internal organs via a magnetic field. Given MRI's non-invasive advantage in repeated imaging, the low-contrast MR images in the target area make segmentation of tissue a challenging pr...

A robust algorithm for explaining unreliable machine learning survival models using the Kolmogorov-Smirnov bounds.

Neural networks : the official journal of the International Neural Network Society
A new robust algorithm based on the explanation method SurvLIME called SurvLIME-KS is proposed for explaining machine learning survival models. The algorithm is developed to ensure robustness to cases of a small amount of training data or outliers of...

Bolus pharmacokinetics: moving beyond mass-based dosing to guide drug administration.

Journal of pharmacokinetics and pharmacodynamics
Despite the common approach of bolus drug dosing using a patient's mass, a more tailored approach would be to use empirically derived pharmacokinetic models. Previously, this could only be possible though the use of computer simulation using programs...

Machine learning in neurosurgery: a global survey.

Acta neurochirurgica
BACKGROUND: Recent technological advances have led to the development and implementation of machine learning (ML) in various disciplines, including neurosurgery. Our goal was to conduct a comprehensive survey of neurosurgeons to assess the acceptance...

Humanoid robot-assisted interventions among children with diabetes: A systematic scoping review.

International journal of nursing studies
BACKGROUND: Although the humanoid robot is highly engaging for children, whether humanoid robot-assisted interventions could help in diabetes management is still unclear.