AIMC Topic: Humans

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Hierarchical motor control in mammals and machines.

Nature communications
Advances in artificial intelligence are stimulating interest in neuroscience. However, most attention is given to discrete tasks with simple action spaces, such as board games and classic video games. Less discussed in neuroscience are parallel advan...

Identifying undetected dementia in UK primary care patients: a retrospective case-control study comparing machine-learning and standard epidemiological approaches.

BMC medical informatics and decision making
BACKGROUND: Identifying dementia early in time, using real world data, is a public health challenge. As only two-thirds of people with dementia now ultimately receive a formal diagnosis in United Kingdom health systems and many receive it late in the...

Biomedical word sense disambiguation with bidirectional long short-term memory and attention-based neural networks.

BMC bioinformatics
BACKGROUND: In recent years, deep learning methods have been applied to many natural language processing tasks to achieve state-of-the-art performance. However, in the biomedical domain, they have not out-performed supervised word sense disambiguatio...

A hybrid self-attention deep learning framework for multivariate sleep stage classification.

BMC bioinformatics
BACKGROUND: Sleep is a complex and dynamic biological process characterized by different sleep patterns. Comprehensive sleep monitoring and analysis using multivariate polysomnography (PSG) records has achieved significant efforts to prevent sleep-re...

Multimodal deep representation learning for protein interaction identification and protein family classification.

BMC bioinformatics
BACKGROUND: Protein-protein interactions(PPIs) engage in dynamic pathological and biological procedures constantly in our life. Thus, it is crucial to comprehend the PPIs thoroughly such that we are able to illuminate the disease occurrence, achieve ...

DeepEP: a deep learning framework for identifying essential proteins.

BMC bioinformatics
BACKGROUND: Essential proteins are crucial for cellular life and thus, identification of essential proteins is an important topic and a challenging problem for researchers. Recently lots of computational approaches have been proposed to handle this p...

A hybrid deep learning framework for bacterial named entity recognition with domain features.

BMC bioinformatics
BACKGROUND: Microbes have been shown to play a crucial role in various ecosystems. Many human diseases have been proved to be associated with bacteria, so it is essential to extract the interaction between bacteria for medical research and applicatio...

Liver tumor segmentation in CT volumes using an adversarial densely connected network.

BMC bioinformatics
BACKGROUND: Malignant liver tumor is one of the main causes of human death. In order to help physician better diagnose and make personalized treatment schemes, in clinical practice, it is often necessary to segment and visualize the liver tumor from ...

Cardio-respiratory signal extraction from video camera data for continuous non-contact vital sign monitoring using deep learning.

Physiological measurement
UNLABELLED: Non-contact vital sign monitoring enables the estimation of vital signs, such as heart rate, respiratory rate and oxygen saturation (SpO), by measuring subtle color changes on the skin surface using a video camera. For patients in a hospi...

Evaluation of colorectal cancer subtypes and cell lines using deep learning.

Life science alliance
Colorectal cancer (CRC) is a common cancer with a high mortality rate and a rising incidence rate in the developed world. Molecular profiling techniques have been used to better understand the variability between tumors and disease models such as cel...