AIMC Topic: Humans

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Robot occupations affect the categorization border between human and robot faces.

Scientific reports
The Uncanny Valley hypothesis implies that people perceive a subjective border between human and robot faces. The robot-human border refers to the level of human-like features that distinguishes humans from robots. However, whether people's perceived...

Deep learning performance for detection and classification of microcalcifications on mammography.

European radiology experimental
BACKGROUND: Breast cancer screening through mammography is crucial for early detection, yet the demand for mammography services surpasses the capacity of radiologists. Artificial intelligence (AI) can assist in evaluating microcalcifications on mammo...

Aided diagnosis of cervical spondylotic myelopathy using deep learning methods based on electroencephalography.

Medical engineering & physics
Cervical spondylotic myelopathy (CSM) is the most severe type of cervical spondylosis. It is challenging to achieve early diagnosis with current clinical diagnostic tools. In this paper, we propose an end-to-end deep learning approach for early diagn...

Cross-Domain Unpaired Learning for Low-Dose CT Imaging.

IEEE journal of biomedical and health informatics
Supervised deep-learning techniques with paired training datasets have been widely studied for low-dose computed tomography (LDCT) imaging with excellent performance. However, the paired training datasets are usually difficult to obtain in clinical r...

Sleep Apnea Prediction Using Deep Learning.

IEEE journal of biomedical and health informatics
Obstructive sleep apnea (OSA) is a sleep disorder that causes partial or complete cessation of breathing during an individual's sleep. Various methods have been proposed to automatically detect OSA events, but little work has focused on predicting su...

Deep Learning in Surgical Workflow Analysis: A Review of Phase and Step Recognition.

IEEE journal of biomedical and health informatics
OBJECTIVE: In the last two decades, there has been a growing interest in exploring surgical procedures with statistical models to analyze operations at different semantic levels. This information is necessary for developing context-aware intelligent ...

Decentralized Data-Privacy Preserving Deep-Learning Approaches for Enhancing Inter-Database Generalization in Automatic Sleep Staging.

IEEE journal of biomedical and health informatics
Automatic sleep staging has been an active field of development. Despite multiple efforts, the area remains a focus of research interest. Indeed, while promising results have reported in past literature, uptake of automatic sleep scoring in the clini...

Individualized Assessment of Brain Aβ Deposition With fMRI Using Deep Learning.

IEEE journal of biomedical and health informatics
PET-based Alzheimer's disease (AD) assessment has many limitations in large-scale screening. Non-invasive techniques such as resting-state functional magnetic resonance imaging (rs-fMRI) have been proven valuable in early AD diagnosis. This study inv...

Semi-Supervised Learning for Low-Cost Personalized Obstructive Sleep Apnea Detection Using Unsupervised Deep Learning and Single-Lead Electrocardiogram.

IEEE journal of biomedical and health informatics
OBJECTIVE: Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder that can lead to a wide range of health issues if left untreated. This study aims to address the lack of research on personalized models for single-lead electrocard...

Digital Twin in Healthcare: A Study for Chronic Wound Management.

IEEE journal of biomedical and health informatics
Although the concept of digital twin technology has been in existence for nearly half a century, its application in healthcare is a relatively recent development. In healthcare, the utilization of digital twin and data-driven models has proven to enh...