AIMC Topic: Humans

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Using machine learning to investigate the relationship between domains of functioning and functional mobility in older adults.

PloS one
Previous studies have shown that functional mobility, along with other physical functions, decreases with advanced age. However, it is still unclear which domains of functioning (body structures, body functions, and activities) are most closely relat...

Artificial Intelligence and Transcatheter Interventions for Structural Heart Disease: A glance at the (near) future.

Trends in cardiovascular medicine
With innovations in therapeutic technologies and changes in population demographics, transcatheter interventions for structural heart disease have become the preferred treatment and will keep growing. Yet, a thorough clinical selection and efficient ...

Neural Networks with Emotion Associations, Topic Modeling and Supervised Term Weighting for Sentiment Analysis.

International journal of neural systems
Automated sentiment analysis is becoming increasingly recognized due to the growing importance of social media and -commerce platform review websites. Deep neural networks outperform traditional lexicon-based and machine learning methods by effective...

Deep learning-based metal artefact reduction in PET/CT imaging.

European radiology
OBJECTIVES: The susceptibility of CT imaging to metallic objects gives rise to strong streak artefacts and skewed information about the attenuation medium around the metallic implants. This metal-induced artefact in CT images leads to inaccurate atte...

Apache Spark based kernelized fuzzy clustering framework for single nucleotide polymorphism sequence analysis.

Computational biology and chemistry
This paper introduces a kernel based fuzzy clustering approach to deal with the non-linear separable problems by applying kernel Radial Basis Functions (RBF) which maps the input data space non-linearly into a high-dimensional feature space. Discover...

Whole-brain modelling of resting state fMRI differentiates ADHD subtypes and facilitates stratified neuro-stimulation therapy.

NeuroImage
Recent advances in non-linear computational and dynamical modelling have opened up the possibility to parametrize dynamic neural mechanisms that drive complex behavior. Importantly, building models of neuronal processes is of key importance to fully ...

Radiomic Machine Learning Classifiers in Spine Bone Tumors: A Multi-Software, Multi-Scanner Study.

European journal of radiology
PURPOSE: Spinal lesion differential diagnosis remains challenging even in MRI. Radiomics and machine learning (ML) have proven useful even in absence of a standardized data mining pipeline. We aimed to assess ML diagnostic performance in spinal lesio...

Machine Learning-Based Automatic Rating for Cardinal Symptoms of Parkinson Disease.

Neurology
OBJECTIVE: We developed and investigated the feasibility of a machine learning-based automated rating for the 2 cardinal symptoms of Parkinson disease (PD): resting tremor and bradykinesia.

Discrimination of malignant from benign thyroid lesions through neural networks using FTIR signals obtained from tissues.

Analytical and bioanalytical chemistry
The current gold standard in cancer diagnosis-the microscopic examination of hematoxylin and eosin (H&E)-stained biopsies-is prone to bias since it greatly relies on visual examination. Hence, there is a need to develop a more sensitive and specific ...

How Robots Help Nurses Focus on Professional Task Engagement and Reduce Nurses' Turnover Intention.

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
PURPOSE: To examine how robot-enabled focus on professional task engagement and robot-reduced nonprofessional task engagement are related to nurses' professional turnover intention.