AIMC Topic: Humans

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AutoAtlas: Neural Network for 3D Unsupervised Partitioning and Representation Learning.

IEEE journal of biomedical and health informatics
We present a novel neural network architecture called AutoAtlas for fully unsupervised partitioning and representation learning of 3D brain Magnetic Resonance Imaging (MRI) volumes. AutoAtlas consists of two neural network components: one neural netw...

Improved and Secured Electromyography in the Internet of Health Things.

IEEE journal of biomedical and health informatics
Physiological signals are of great importance for clinical analysis but are prone to diverse interferences. To enable practical applications, biosignal quality issues, especially contaminants, need to be dealt with automated processes. For example, a...

Preserving the Privacy of Healthcare Data over Social Networks Using Machine Learning.

Computational intelligence and neuroscience
A key challenge in clinical recommendation systems is the problem of aberrant patient profiles in social networks. As a result of a person's abnormal profile, numerous vests might be used to make fake remarks about them, cyber bullying, or cyber-atta...

An Improved BERT and Syntactic Dependency Representation Model for Sentiment Analysis.

Computational intelligence and neuroscience
Text representation of social media is an important task for users' sentiment analysis. Utilizing the better representation, we can accurately acquire the real semantic information expressed by online users. However, existing works cannot achieve the...

A survival analysis based volatility and sparsity modeling network for student dropout prediction.

PloS one
Student Dropout Prediction (SDP) is pivotal in mitigating withdrawals in Massive Open Online Courses. Previous studies generally modeled the SDP problem as a binary classification task, providing a single prediction outcome. Accordingly, some attempt...

Breast cancer histopathological images classification based on deep semantic features and gray level co-occurrence matrix.

PloS one
Breast cancer is regarded as the leading killer of women today. The early diagnosis and treatment of breast cancer is the key to improving the survival rate of patients. A method of breast cancer histopathological images recognition based on deep sem...

Noise exposure during robot-assisted total knee arthroplasty.

Archives of orthopaedic and trauma surgery
The aim of the study was to examine the noise exposure for operating theater staff during total knee arthroplasty (TKA) with three different robot systems. There is already evidence that noise exposure during TKA performed manually exceeds recommende...

Increasing angular sampling through deep learning for stationary cardiac SPECT image reconstruction.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: The GE Discovery NM (DNM) 530c/570c are dedicated cardiac SPECT scanners with 19 detector modules designed for stationary imaging. This study aims to incorporate additional projection angular sampling to improve reconstruction quality. A ...

Robotic versus Laparoscopic Total Mesorectal Excision Surgery in Rectal Cancer: Analysis of Medium-Term Oncological Outcomes.

Surgical innovation
. Robotic systems can overcome some limitations of laparoscopic total mesorectal excision (L-TME), thus improving the quality of the surgery. So far, many studies have reported the technical feasibility and short-term oncological results of robotic t...