AIMC Topic: Humans

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Experimental demonstration of highly reliable dynamic memristor for artificial neuron and neuromorphic computing.

Nature communications
Neuromorphic computing, a computing paradigm inspired by the human brain, enables energy-efficient and fast artificial neural networks. To process information, neuromorphic computing directly mimics the operation of biological neurons in a human brai...

Effects of control strategies on gait in robot-assisted post-stroke lower limb rehabilitation: a systematic review.

Journal of neuroengineering and rehabilitation
BACKGROUND: Stroke related motor function deficits affect patients' likelihood of returning to professional activities, limit their participation in society and functionality in daily living. Hence, robot-aided gait rehabilitation needs to be fruitfu...

Soft robotic exosuit augmented high intensity gait training on stroke survivors: a pilot study.

Journal of neuroengineering and rehabilitation
BACKGROUND: Stroke is a leading cause of serious gait impairments and restoring walking ability is a major goal of physical therapy interventions. Soft robotic exosuits are portable, lightweight, and unobtrusive assistive devices designed to improve ...

Decisions are not all equal-Introducing a utility metric based on case-wise raters' perceptions.

Computer methods and programs in biomedicine
Background and Objective Evaluation of AI-based decision support systems (AI-DSS) is of critical importance in practical applications, nonetheless common evaluation metrics fail to properly consider relevant and contextual information. In this articl...

Multi-Level Functional Connectivity Fusion Classification Framework for Brain Disease Diagnosis.

IEEE journal of biomedical and health informatics
Brain disease diagnosis is a new hotspot in the cross research of artificial intelligence and neuroscience. Quantitative analysis of functional magnetic resonance imaging (fMRI) data can provide valuable biomarkers that contributes to clinical diagno...

Personalized On-Device E-Health Analytics With Decentralized Block Coordinate Descent.

IEEE journal of biomedical and health informatics
Actuated by the growing attention to personal healthcare and the pandemic, the popularity of E-health is proliferating. Nowadays, enhancement on medical diagnosis via machine learning models has been highly effective in many aspects of e-health analy...

Uncertainty-Aware Deep Learning With Cross-Task Supervision for PHE Segmentation on CT Images.

IEEE journal of biomedical and health informatics
Perihematomal edema (PHE) volume, surrounding spontaneous intracerebral hemorrhage (SICH), is an important biomarker for the presence of SICH-associated diseases. However, due to irregular shapes and extremely low contrast of PHE on CT images, manual...

AL-Net: Attention Learning Network Based on Multi-Task Learning for Cervical Nucleus Segmentation.

IEEE journal of biomedical and health informatics
Cervical nucleus segmentation is a crucial and challenging issue in automatic pathological diagnosis due to uneven staining, blurry boundaries, and adherent or overlapping nuclei in nucleus images. To overcome the limitation of current methods, we pr...