AIMC Topic: Male

Clear Filters Showing 10541 to 10550 of 27433 articles

A deep learning approach for generating intracranial pressure waveforms from extracranial signals routinely measured in the intensive care unit.

Computers in biology and medicine
Intracranial pressure (ICP) is commonly monitored to guide treatment in patients with serious brain disorders such as traumatic brain injury and stroke. Established methods to assess ICP are resource intensive and highly invasive. We hypothesized tha...

No playing around with robots? Ambivalent attitudes toward the use of Paro in elder care.

Nursing inquiry
This paper explores the ways in which health care professionals, family carers, and older persons expressed attitudes and opinions on using Paro, a social robot designed to stimulate patients with dementia. Thereafter, we critically evaluate existing...

Deep Learning-Based Facial and Skeletal Transformations for Surgical Planning.

Journal of dental research
The increasing application of virtual surgical planning (VSP) in orthognathic surgery implies a critical need for accurate prediction of facial and skeletal shapes. The craniofacial relationship in patients with dentofacial deformities is still not u...

Development and Validation of a Machine Learning Model to Predict Weekly Risk of Hypoglycemia in Patients with Type 1 Diabetes Based on Continuous Glucose Monitoring.

Diabetes technology & therapeutics
The aim of this study was to develop and validate a prediction model based on continuous glucose monitoring (CGM) data to identify a week-to-week risk profile of excessive hypoglycemia. We analyzed, trained, and internally tested two prediction mod...

Towards a machine-learning assisted non-invasive classification of dengue severity using wearable PPG data: a prospective clinical study.

EBioMedicine
BACKGROUND: Dengue epidemics impose considerable strain on healthcare resources. Real-time continuous and non-invasive monitoring of patients admitted to the hospital could lead to improved care and outcomes. We evaluated the performance of a commerc...

Combining Sound and Deep Neural Networks for the Measurement of Jump Height in Sports Science.

Sensors (Basel, Switzerland)
Jump height tests are employed to measure lower-limb muscle power of athletic and non-athletic populations. The most popular instruments for this purpose are jump mats and, in recent years, smartphone apps, which compute jump height through the manua...

Investigation of Motor Learning Effects Using a Hybrid Rehabilitation System Based on Motion Estimation.

Sensors (Basel, Switzerland)
Upper-limb paralysis requires extensive rehabilitation to recover functionality for everyday living, and such assistance can be supported with robot technology. Against such a background, we have proposed an electromyography (EMG)-driven hybrid rehab...

Predicting Non-Alcoholic Steatohepatitis: A Lipidomics-Driven Machine Learning Approach.

International journal of molecular sciences
Nonalcoholic fatty liver disease (NAFLD), nowadays the most prevalent chronic liver disease in Western countries, is characterized by a variable phenotype ranging from steatosis to nonalcoholic steatohepatitis (NASH). Intracellular lipid accumulation...

Deep learning model for differentiating nasal cavity masses based on nasal endoscopy images.

BMC medical informatics and decision making
BACKGROUND: Nasal polyps and inverted papillomas often look similar. Clinically, it is difficult to distinguish the masses by endoscopic examination. Therefore, in this study, we aimed to develop a deep learning algorithm for computer-aided diagnosis...

An ensemble-based machine learning model for predicting type 2 diabetes and its effect on bone health.

BMC medical informatics and decision making
BACKGROUND: Diabetes is a chronic condition that can result in many long-term physiological, metabolic, and neurological complications. Therefore, early detection of diabetes would help to determine a proper diagnosis and treatment plan.