AIMC Topic: Humans

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Workflow for automatic renal perfusion quantification using ASL-MRI and machine learning.

Magnetic resonance in medicine
PURPOSE: Clinical applicability of renal arterial spin labeling (ASL) MRI is hampered because of time consuming and observer dependent post-processing, including manual segmentation of the cortex to obtain cortical renal blood flow (RBF). Machine lea...

The importance of developing care-worker-centered robotic aides in long-term care.

Bioethics
Recent research points to the fact that new medical technological innovations are just as relevant in the context of long-term care or chronic care as they are in the context of acute care. In the spirit of the Nuffield Foundation recommendations, th...

Brain functional and effective connectivity based on electroencephalography recordings: A review.

Human brain mapping
Functional connectivity and effective connectivity of the human brain, representing statistical dependence and directed information flow between cortical regions, significantly contribute to the study of the intrinsic brain network and its functional...

Radiomic machine learning for pretreatment assessment of prognostic risk factors for endometrial cancer and its effects on radiologists' decisions of deep myometrial invasion.

Magnetic resonance imaging
PURPOSE: To evaluate radiomic machine learning (ML) classifiers based on multiparametric magnetic resonance images (MRI) in pretreatment assessment of endometrial cancer (EC) risk factors and to examine effects on radiologists' interpretation of deep...

Deep-learning-based synthesis of post-contrast T1-weighted MRI for tumour response assessment in neuro-oncology: a multicentre, retrospective cohort study.

The Lancet. Digital health
BACKGROUND: Gadolinium-based contrast agents (GBCAs) are widely used to enhance tissue contrast during MRI scans and play a crucial role in the management of patients with cancer. However, studies have shown gadolinium deposition in the brain after r...

Prediction of Micronucleus Assay Outcome Using In Vivo Activity Data and Molecular Structure Features.

Applied biochemistry and biotechnology
In vivo micronucleus assay is the widely used genotoxic test to determine the extent of chromosomal aberrations caused by the chemicals in human beings, which plays a significant role in the drug discovery paradigm. To reduce the uncertainties of the...

Design of a Data Glove for Assessment of Hand Performance Using Supervised Machine Learning.

Sensors (Basel, Switzerland)
The large number of poststroke recovery patients poses a burden on rehabilitation centers, hospitals, and physiotherapists. The advent of rehabilitation robotics and automated assessment systems can ease this burden by assisting in the rehabilitation...

Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review.

BMJ (Clinical research ed.)
OBJECTIVE: To assess the methodological quality of studies on prediction models developed using machine learning techniques across all medical specialties.

Artificial intelligence as a diagnostic aid in cross-sectional radiological imaging of the abdominopelvic cavity: a protocol for a systematic review.

BMJ open
INTRODUCTION: The application of artificial intelligence (AI) technologies as a diagnostic aid in healthcare is increasing. Benefits include applications to improve health systems, such as rapid and accurate interpretation of medical images. This may...