AIMC Topic: Aged

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An artificial neural network model for clinical score prediction in Alzheimer disease using structural neuroimaging measures.

Journal of psychiatry & neuroscience : JPN
BACKGROUND: The development of diagnostic and prognostic tools for Alzheimer disease is complicated by substantial clinical heterogeneity in prodromal stages. Many neuroimaging studies have focused on case–control classification and predicting conver...

A Predictive Model for Determining Patients Not Requiring Prolonged Hospital Length of Stay After Elective Primary Total Hip Arthroplasty.

Anesthesia and analgesia
BACKGROUND: Hospital length of stay (LOS) is an important quality metric for total hip arthroplasty. Accurately predicting LOS is important to expectantly manage bed utilization and other hospital resources. We aimed to develop a predictive model for...

Detection of Brain Activation in Unresponsive Patients with Acute Brain Injury.

The New England journal of medicine
BACKGROUND: Brain activation in response to spoken motor commands can be detected by electroencephalography (EEG) in clinically unresponsive patients. The prevalence and prognostic importance of a dissociation between commanded motor behavior and bra...

Method for Muscle Tone Monitoring During Robot-Assisted Therapy of Hand Function: A Proof of Concept.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Robot-assisted rehabilitation of hand function is becoming an established approach to complement conventional therapy after stroke, particularly in view of its possible unsupervised use to promote an increase in therapy dose. Given their intensive th...

A robot-assisted sensorimotor training program can improve proprioception and motor function in stroke survivors.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Proprioceptive deficits are common among stroke survivors and are associated with slower motor recovery, poorer upper limb motor function, and decreased self-care ability. Somatosensory feedback augmenting proprioception should enhance motor control ...

Robot-based assessment of sitting and standing balance: preliminary results in Parkinson's disease.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Postural responses to unstable conditions or perturbations are important predictors of the risk of falling and can reveal balance deficits in people with neurological disorders, such as Parkinson's Disease (PD). However, there is a lack of evidences ...

A Human-assistive Robotic Platform with Quadrupedal Locomotion.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Mobility impairment is becoming a challenging issue around the world with a rapid increase on aging population. Existing tools of walking assistance for mobility-impaired people include passive canes or wheeled rollators which increase energy consump...

Towards an Adaptive Upper Limb Rehabilitation Game with Tangible Robots.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
A key feature of a successful game is its ability to provide the player with an adequate level of challenge. However, the objective of difficulty adaptation in serious games is not only to maintain the player's motivation by challenging, but also to ...

Application of deep learning (3-dimensional convolutional neural network) for the prediction of pathological invasiveness in lung adenocarcinoma: A preliminary study.

Medicine
To compare results for radiological prediction of pathological invasiveness in lung adenocarcinoma between radiologists and a deep learning (DL) system.Ninety patients (50 men, 40 women; mean age, 66 years; range, 40-88 years) who underwent pre-opera...

Can Machine Learning Algorithms Predict Which Patients Will Achieve Minimally Clinically Important Differences From Total Joint Arthroplasty?

Clinical orthopaedics and related research
BACKGROUND: Identifying patients at risk of not achieving meaningful gains in long-term postsurgical patient-reported outcome measures (PROMs) is important for improving patient monitoring and facilitating presurgical decision support. Machine learni...