AI Medical Compendium Topic

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Muscle, Skeletal

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Validation of a deep learning segmentation algorithm to quantify the skeletal muscle index and sarcopenia in metastatic renal carcinoma.

European radiology
OBJECTIVES: To validate a deep learning (DL) algorithm for measurement of skeletal muscular index (SMI) and prediction of overall survival in oncology populations.

A deep learning tool without muscle-by-muscle grading to differentiate myositis from facio-scapulo-humeral dystrophy using MRI.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to assess the capabilities of a deep learning (DL) tool to discriminate between type 1 facioscapulo-humeral dystrophy (FSHD1) and myositis using whole-body muscle magnetic resonance imaging (MRI) examination wit...

Recurrent neural network to predict hyperelastic constitutive behaviors of the skeletal muscle.

Medical & biological engineering & computing
Hyperelastic constitutive laws have been commonly used to model the passive behavior of the human skeletal muscle. Despite many efforts, the use of accurate finite element formulations of hyperelastic constitutive laws is still time-consuming for a r...

Convolutional LSTM: a deep learning approach to predict shoulder joint reaction forces.

Computer methods in biomechanics and biomedical engineering
We developed a Convolutional LSTM (ConvLSTM) network to predict shoulder joint reaction forces using 3D shoulder kinematics data containing 30 different shoulder activities from eight human subjects. We considered simulation outcomes from the AnyBody...

Defining Normal Ranges of Skeletal Muscle Area and Skeletal Muscle Index in Children on CT Using an Automated Deep Learning Pipeline: Implications for Sarcopenia Diagnosis.

AJR. American journal of roentgenology
Skeletal muscle area (SMA), representing skeletal muscle cross-sectional area at the L3 vertebral level, and skeletal muscle index (SMI), representing height-normalized SMA, can serve as markers of sarcopenia. Normal SMA and SMI values have been rep...

A generic neural network model to estimate populational neural activity for robust neural decoding.

Computers in biology and medicine
BACKGROUND: Robust and continuous neural decoding is crucial for reliable and intuitive neural-machine interactions. This study developed a novel generic neural network model that can continuously predict finger forces based on decoded populational m...

Actuation-Augmented Biohybrid Robot by Hyaluronic Acid-Modified Au Nanoparticles in Muscle Bundles to Evaluate Drug Effects.

ACS sensors
Biohybrid robots, which comprise soft materials with biological components, have the potential to sense, respond, and adapt to changing environmental loads dynamically. Instead of humans and other living things, biohybrid robots can be used in variou...

Adaptive biohybrid pumping machine with flow loop feedback.

Biofabrication
Tissue-engineered living machines is an emerging discipline that employs complex interactions between living cells and engineered scaffolds to self-assemble biohybrid systems for diverse scientific research and technological applications. Here, we re...

Humanoid Robot Based Platform to Evaluate the Efficacy of Using Inertial Sensors for Spasticity Assessment in Cerebral Palsy.

IEEE journal of biomedical and health informatics
Spasticity is commonly present in individuals with cerebral palsy (CP) and manifests itself as shaky movements, muscle tightness and joint stiffness. Accurate and objective measurement of spasticity is investigated using inertial measurement unit (IM...