AIMC Topic: Humans

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Artificial intelligence to improve efficiency of administration of gross motor function assessment in children with cerebral palsy.

Developmental medicine and child neurology
AIM: To create a reduced version of the 66-item Gross Motor Function Measure (rGMFM-66) using innovative artificial intelligence methods to improve efficiency of administration of the GMFM-66.

Feature-fusion improves MRI single-shot deep learning detection of small brain metastases.

Journal of neuroimaging : official journal of the American Society of Neuroimaging
BACKGROUND AND PURPOSE: To examine whether feature-fusion (FF) method improves single-shot detector's (SSD's) detection of small brain metastases on contrast-enhanced (CE) T1-weighted MRI.

Schematic memory persistence and transience for efficient and robust continual learning.

Neural networks : the official journal of the International Neural Network Society
Continual learning is considered a promising step toward next-generation Artificial Intelligence (AI), where deep neural networks (DNNs) make decisions by continuously learning a sequence of different tasks akin to human learning processes. It is sti...

Can Deep Learning Algorithms Help Identify Surgical Workflow and Techniques?

The Journal of surgical research
BACKGROUND: Surgical videos are now being used for performance review and educational purposes; however, broad use is still limited due to time constraints. To make video review more efficient, we implemented Artificial Intelligence (AI) algorithms t...

Predicting Incident Heart Failure in Women With Machine Learning: The Women's Health Initiative Cohort.

The Canadian journal of cardiology
BACKGROUND: Heart failure (HF) is a leading cause of cardiac morbidity among women, whose risk factors differ from those in men. We used machine-learning approaches to develop risk- prediction models for incident HF in a cohort of postmenopausal wome...

Accounting for symptom heterogeneity can improve neuroimaging models of antidepressant response after electroconvulsive therapy.

Human brain mapping
Depression symptom heterogeneity limits the identifiability of treatment-response biomarkers. Whether improvement along dimensions of depressive symptoms relates to separable neural networks remains poorly understood. We build on work describing thre...

Deep learning enabled brain shunt valve identification using mobile phones.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Accurate information concerning implanted medical devices prior to a Magnetic resonance imaging (MRI) examination is crucial to assure safety of the patient and to address MRI induced unintended changes in device settings. T...

Feature selection for unsupervised machine learning of accelerometer data physical activity clusters - A systematic review.

Gait & posture
BACKGROUND: Identifying clusters of physical activity (PA) from accelerometer data is important to identify levels of sedentary behaviour and physical activity associated with risks of serious health conditions and time spent engaging in healthy PA. ...

Impact of artificial intelligence on clinical radiography practice: Futuristic prospects in a low resource setting.

Radiography (London, England : 1995)
OBJECTIVES: Current trends in clinical radiography practice include the integration of artificial intelligence (AI) and related applications to improve patient care and enhance research. However, in low resource countries there are unique barriers to...