AIMC Topic: Humans

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Automated classification of clinical trial eligibility criteria text based on ensemble learning and metric learning.

BMC medical informatics and decision making
BACKGROUND: Eligibility criteria are the primary strategy for screening the target participants of a clinical trial. Automated classification of clinical trial eligibility criteria text by using machine learning methods improves recruitment efficienc...

CapsTM: capsule network for Chinese medical text matching.

BMC medical informatics and decision making
BACKGROUND: Text Matching (TM) is a fundamental task of natural language processing widely used in many application systems such as information retrieval, automatic question answering, machine translation, dialogue system, reading comprehension, etc....

Transformers-sklearn: a toolkit for medical language understanding with transformer-based models.

BMC medical informatics and decision making
BACKGROUND: Transformer is an attention-based architecture proven the state-of-the-art model in natural language processing (NLP). To reduce the difficulty of beginning to use transformer-based models in medical language understanding and expand the ...

The future of bone regeneration: integrating AI into tissue engineering.

Biomedical physics & engineering express
Tissue engineering is a branch of regenerative medicine that harnesses biomaterial and stem cell research to utilise the body's natural healing responses to regenerate tissue and organs. There remain many unanswered questions in tissue engineering, w...

Evaluation Model of Physical Education Effect: On the Application of Radial Basis Function-Particle Swarm Optimization Neural Network (RBFNN-PSO).

Computational intelligence and neuroscience
This study constructs a new radial basis function-particle swarm optimization neural network (RBFNN-PSO) system, which is applied to the evaluation system of physical education teaching effect. In order to verify the evaluation performance of the RBF...

Deep learning with robustness to missing data: A novel approach to the detection of COVID-19.

PloS one
In the context of the current global pandemic and the limitations of the RT-PCR test, we propose a novel deep learning architecture, DFCN (Denoising Fully Connected Network). Since medical facilities around the world differ enormously in what laborat...

Rapid whole-brain electric field mapping in transcranial magnetic stimulation using deep learning.

PloS one
Transcranial magnetic stimulation (TMS) is a non-invasive neurostimulation technique that is increasingly used in the treatment of neuropsychiatric disorders and neuroscience research. Due to the complex structure of the brain and the electrical cond...

Body shape matters: Evidence from machine learning on body shape-income relationship.

PloS one
The association between physical appearance and income has been of central interest in social science. However, most previous studies often measured physical appearance using classical proxies from subjective opinions based on surveys. In this study,...

Estimating Human Pose Efficiently by Parallel Pyramid Networks.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Good performance and high efficiency are both critical for estimating human pose in practice. Recent state-of-the-art methods have greatly boosted the pose detection accuracy through deep convolutional neural networks, however, the strong performance...

The Role of Artificial Intelligence and Machine Learning in Clinical Cardiac Electrophysiology.

The Canadian journal of cardiology
In recent years, numerous applications for artificial intelligence (AI) in cardiology have been found, due in part to large digitized data sets and the evolution of high-performance computing. In the discipline of cardiac electrophysiology (EP), a nu...