AIMC Topic: Female

Clear Filters Showing 18441 to 18450 of 29210 articles

Identification of patients with and without minimal hepatic encephalopathy based on gray matter volumetry using a support vector machine learning algorithm.

Scientific reports
Minimal hepatic encephalopathy (MHE) is characterized by diffuse abnormalities in cerebral structure, such as reduced cortical thickness and altered brain parenchymal volume. This study tested the potential of gray matter (GM) volumetry to differenti...

Multimodal Data Analysis of Alzheimer's Disease Based on Clustering Evolutionary Random Forest.

IEEE journal of biomedical and health informatics
Alzheimer's disease (AD) has become a severe medical challenge. Advances in technologies produced high-dimensional data of different modalities including functional magnetic resonance imaging (fMRI) and single nucleotide polymorphism (SNP). Understan...

Effects of interactive robot-enhanced hand rehabilitation in treatment of paediatric hand-burns: A randomized, controlled trial with 3-months follow-up.

Burns : journal of the International Society for Burn Injuries
PURPOSE: To evaluate the effectiveness of the robotic-assisted exercise with virtual gaming on total active range of motion (ROM) of the digits, hand grip strength (HGS), and hand function in children with hand burns.

Prehospital triage of acute aortic syndrome using a machine learning algorithm.

The British journal of surgery
BACKGROUND: Acute aortic syndrome (AAS) comprises a complex and potentially fatal group of conditions requiring emergency specialist management. The aim of this study was to build a prediction algorithm to assist prehospital triage of AAS.

Detecting total hip replacement prosthesis design on plain radiographs using deep convolutional neural network.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Identifying the design of a failed implant is a key step in the preoperative planning of revision total joint arthroplasty. Manual identification of the implant design from radiographic images is time-consuming and prone to error. Failure to identify...

Gait variability as digital biomarker of disease severity in Huntington's disease.

Journal of neurology
BACKGROUND: Impaired gait plays an important role for quality of life in patients with Huntington's disease (HD). Measuring objective gait parameters in HD might provide an unbiased assessment of motor deficits in order to determine potential benefic...

Decoding rejuvenating effects of mechanical loading on skeletal aging using in vivo μCT imaging and deep learning.

Acta biomaterialia
Throughout the process of aging, dynamic changes of bone material, micro- and macro-architecture result in a loss of strength and therefore in an increased likelihood of fragility fractures. To date, precise contributions of age-related changes in bo...

Application of Machine Learning in Developing a Novelty Five-Pseudogene Signature to Predict Prognosis of Head and Neck Squamous Cell Carcinoma: A New Aspect of "Junk Genes" in Biomedical Practice.

DNA and cell biology
Head and neck squamous cell carcinoma (HNSCC) is the sixth malignancy, which is characterized by poor prognosis or high mortality because of the lack of predicting markers. Aberrant cancer pseudogenes have been found predictive for prognosis. We aim ...

Deep Learning for Automatic Calcium Scoring in CT: Validation Using Multiple Cardiac CT and Chest CT Protocols.

Radiology
Background Although several deep learning (DL) calcium scoring methods have achieved excellent performance for specific CT protocols, their performance in a range of CT examination types is unknown. Purpose To evaluate the performance of a DL method ...

Predicting sporadic Alzheimer's disease progression via inherited Alzheimer's disease-informed machine-learning.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Developing cross-validated multi-biomarker models for the prediction of the rate of cognitive decline in Alzheimer's disease (AD) is a critical yet unmet clinical challenge.