AIMC Topic: Reproducibility of Results

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Toward Robust, Adaptiveand Reliable Upper-Limb Motion Estimation Using Machine Learning and Deep Learning-A Survey in Myoelectric Control.

IEEE journal of biomedical and health informatics
To develop multi-functionalhuman-machine interfaces that can help disabled people reconstruct lost functions of upper-limbs, machine learning (ML) and deep learning (DL) techniques have been widely implemented to decode human movement intentions from...

Deep Learning Estimation of Median Nerve Volume Using Ultrasound Imaging in a Human Cadaver Model.

Ultrasound in medicine & biology
Median nerve swelling is one of the features of carpal tunnel syndrome (CTS), and ultrasound measurement of maximum median nerve cross-sectional area is commonly used to diagnose CTS. We hypothesized that volume might be a more sensitive measure than...

Deep Learning Mechanism for Predicting the Axillary Lymph Node Metastasis in Patients with Primary Breast Cancer.

BioMed research international
The second largest cause of mortality worldwide is breast cancer, and it mostly occurs in women. Early diagnosis has improved further treatments and reduced the level of mortality. A unique deep learning algorithm is presented for predicting breast c...

Does a deep learning inventory predict knowledge transfer? Linking student perceptions to transfer outcomes.

Advances in health sciences education : theory and practice
Students are often encouraged to learn 'deeply' by abstracting generalizable principles from course content rather than memorizing details. So widespread is this perspective that Likert-style inventories are now routinely administered to students to ...

Advances in Emerging Photonic Memristive and Memristive-Like Devices.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Possessing the merits of high efficiency, low consumption, and versatility, emerging photonic memristive and memristive-like devices exhibit an attractive future in constructing novel neuromorphic computing and miniaturized bionic electronic system. ...

Predicting Mortality in Intensive Care Unit Patients With Heart Failure Using an Interpretable Machine Learning Model: Retrospective Cohort Study.

Journal of medical Internet research
BACKGROUND: Heart failure (HF) is a common disease and a major public health problem. HF mortality prediction is critical for developing individualized prevention and treatment plans. However, due to their lack of interpretability, most HF mortality ...

Real Estate Tax Base Assessment by Deep Learning Neural Network in the Context of the Digital Economy.

Computational intelligence and neuroscience
With the continuous development of China's digital economy and the continuous heating of the real estate market, real estate tax base assessment occupies an important position in the real estate market. The purpose is to improve the work efficiency o...

Early prediction of noninvasive ventilation failure after extubation: development and validation of a machine-learning model.

BMC pulmonary medicine
BACKGROUND: Noninvasive ventilation (NIV) has been widely used in critically ill patients after extubation. However, NIV failure is associated with poor outcomes. This study aimed to determine early predictors of NIV failure and to construct an accur...

Named Entity Aware Transfer Learning for Biomedical Factoid Question Answering.

IEEE/ACM transactions on computational biology and bioinformatics
Biomedical factoid question answering is an important task in biomedical question answering applications. It has attracted much attention because of its reliability. In question answering systems, better representation of words is of great importance...

A fully stapled technique for gastrojejunal anastomosis creation in robotic Roux-en-Y gastric bypass.

Langenbeck's archives of surgery
PURPOSE: The purpose of this paper is to showcase a fully stapled approach to creating a gastrojejunostomy during a robot-assisted Roux-en-Y gastric bypass.