AIMC Topic: Humans

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Multivariate resting-state functional connectivity predicts responses to real and sham acupuncture treatment in chronic low back pain.

NeuroImage. Clinical
Despite the high prevalence and socioeconomic impact of chronic low back pain (cLBP), treatments for cLBP are often unsatisfactory, and effectiveness varies widely across patients. Recent neuroimaging studies have demonstrated abnormal resting-state ...

Gradually focused fine-grained sketch-based image retrieval.

PloS one
This paper focuses on fine-grained image retrieval based on sketches. Sketches capture detailed information, but their highly abstract nature makes visual comparisons with images more difficult. In spite of the fact that the existing models take into...

Computational approaches and machine learning for individual-level treatment predictions.

Psychopharmacology
RATIONALE: The impact of neuroscience-based approaches for psychiatry on pragmatic clinical decision-making has been limited. Although neuroscience has provided insights into basic mechanisms of neural function, these insights have not improved the a...

Robust RGB-D Face Recognition Using Attribute-Aware Loss.

IEEE transactions on pattern analysis and machine intelligence
Existing convolutional neural network (CNN) based face recognition algorithms typically learn a discriminative feature mapping, using a loss function that enforces separation of features from different classes and/or aggregation of features within th...

Grading of Clear Cell Renal Cell Carcinomas by Using Machine Learning Based on Artificial Neural Networks and Radiomic Signatures Extracted From Multidetector Computed Tomography Images.

Academic radiology
RATIONALE AND OBJECTIVES: To evaluate the ability of artificial neural networks (ANN) fed with radiomic signatures (RSs) extracted from multidetector computed tomography images in differentiating the histopathological grades of clear cell renal cell ...

Deep learning for cellular image analysis.

Nature methods
Recent advances in computer vision and machine learning underpin a collection of algorithms with an impressive ability to decipher the content of images. These deep learning algorithms are being applied to biological images and are transforming the a...

Deep Sequential Models for Suicidal Ideation From Multiple Source Data.

IEEE journal of biomedical and health informatics
This paper presents a novel method for predicting suicidal ideation from electronic health records (EHR) and ecological momentary assessment (EMA) data using deep sequential models. Both EHR longitudinal data and EMA question forms are defined by asy...

Assessing the concurrent validity of a gait analysis system integrated into a smart walker in older adults with gait impairments.

Clinical rehabilitation
OBJECTIVE: To assess the concurrent validity of a smart walker-integrated gait analysis system with the GAITRite system for measuring spatiotemporal gait parameters in potential users of the smart walker.