AIMC Topic: Adult

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Principles and Validations of an Artificial Intelligence-Based Recommender System Suggesting Acceptable Food Changes.

The Journal of nutrition
BACKGROUND: Along with the popularity of smartphones, artificial intelligence-based personalized suggestions can be seen as promising ways to change eating habits toward more desirable diets.

Fully automatic volume measurement of the adrenal gland on CT using deep learning to classify adrenal hyperplasia.

European radiology
OBJECTIVES: To develop a fully automated deep learning model for adrenal segmentation and to evaluate its performance in classifying adrenal hyperplasia.

Development and validation of a machine learning algorithm for predicting diffuse midline glioma, H3 K27-altered, H3 K27 wild-type high-grade glioma, and primary CNS lymphoma of the brain midline in adults.

Journal of neurosurgery
OBJECTIVE: Preoperative diagnosis of diffuse midline glioma, H3 K27-altered (DMG-A) and midline high-grade glioma without H3 K27 alteration (DMG-W), as well as midline primary CNS lymphoma (PCNSL) in adults, is challenging but crucial. The aim of thi...

Detecting defense mechanisms from Adult Attachment Interview (AAI) transcripts using machine learning.

Psychotherapy research : journal of the Society for Psychotherapy Research
OBJECTIVE: Defensive functioning (i.e., unconscious process used to manage real or perceived threats) may play a role in the development of various psychopathologies. It is typically assessed via observer rating measures, however, human coding of def...

Reliability of active robotic neuro-navigated transcranial magnetic stimulation motor maps.

Experimental brain research
Transcranial magnetic stimulation (TMS) motor mapping is a safe, non-invasive method used to study corticomotor organization and intervention-induced plasticity. Reliability of resting maps is well established, but understudied for active maps and un...

Role of deep learning methods in screening for subcutaneous implantable cardioverter defibrillator in heart failure.

Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc
INTRODUCTION: S-ICD eligibility is assessed at pre-implant screening where surface ECG traces are used as surrogates for S-ICD vectors. In heart failure (HF) patients undergoing diuresis, electrolytes and fluid shifts can cause changes in R and T wav...

Application of Machine Learning to Child Mode Choice with a Novel Technique to Optimize Hyperparameters.

International journal of environmental research and public health
Travel mode choice (TMC) prediction is crucial for transportation planning. Most previous studies have focused on TMC in adults, whereas predicting TMC in children has received less attention. On the other hand, previous children's TMC prediction stu...

Predicting multipotency of human adult stem cells derived from various donors through deep learning.

Scientific reports
Adult stem cell-based therapeutic approaches have great potential in regenerative medicine because of their immunoregulatory properties and multidifferentiation capacity. Nevertheless, the outcomes of stem cell‑based therapies to date have shown inco...

A Machine Learning-Based Approach to Predict Prognosis and Length of Hospital Stay in Adults and Children With Traumatic Brain Injury: Retrospective Cohort Study.

Journal of medical Internet research
BACKGROUND: The treatment and care of adults and children with traumatic brain injury (TBI) constitute an intractable global health problem. Predicting the prognosis and length of hospital stay of patients with TBI may improve therapeutic effects and...

Feasibility and Safety of a Powered Exoskeleton for Balance Training for People Living with Multiple Sclerosis: A Single-Group Preliminary Study (Rapper III).

Journal of rehabilitation medicine
OBJECTIVE: To evaluate the feasibility, usability, safety, and potential health benefits of using an exoskeleton device for rehabilitation of people living with multiple sclerosis.