AIMC Topic: Adult

Clear Filters Showing 9771 to 9780 of 15606 articles

Evaluation of Glomerular Filtration Rate in Chronic Kidney Disease by Radial Basis Function Neural Network.

Transplantation proceedings
OBJECTIVE: To develop a radial basis function (RBF) neural network and investigate its performance in the estimation of glomerular filtration rate (GFR) for patients with chronic kidney disease.

Artificial intelligence in fixed implant prosthodontics: a retrospective study of 106 implant-supported monolithic zirconia crowns inserted in the posterior jaws of 90 patients.

BMC oral health
BACKGROUND: Artificial intelligence (AI) is a branch of computer science concerned with building smart software or machines capable of performing tasks that typically require human intelligence. We present a protocol for the use of AI to fabricate im...

Deep learning approaches for sleep disorder prediction in an asthma cohort.

The Journal of asthma : official journal of the Association for the Care of Asthma
OBJECTIVE: Sleep is a natural activity of humans that affects physical and mental health; therefore, sleep disturbance may lead to fatigue and lower productivity. This study examined 1 million samples included in the Taiwan National Health Insurance ...

Interpatient Similarities in Cardiac Function: A Platform for Personalized Cardiovascular Medicine.

JACC. Cardiovascular imaging
OBJECTIVES: The authors applied unsupervised machine-learning techniques for integrating echocardiographic features of left ventricular (LV) structure and function into a patient similarity network that predicted major adverse cardiac event(s) (MACE)...

Toward a unified framework for interpreting machine-learning models in neuroimaging.

Nature protocols
Machine learning is a powerful tool for creating computational models relating brain function to behavior, and its use is becoming widespread in neuroscience. However, these models are complex and often hard to interpret, making it difficult to evalu...

Identifying predictive features of autism spectrum disorders in a clinical sample of adolescents and adults using machine learning.

Scientific reports
Diagnosing autism spectrum disorders (ASD) is a complicated, time-consuming process which is particularly challenging in older individuals. One of the most widely used behavioral diagnostic tools is the Autism Diagnostic Observation Schedule (ADOS). ...

A convolutional neural network-based system to classify patients using FDG PET/CT examinations.

BMC cancer
BACKGROUND: As the number of PET/CT scanners increases and FDG PET/CT becomes a common imaging modality for oncology, the demands for automated detection systems on artificial intelligence (AI) to prevent human oversight and misdiagnosis are rapidly ...

Novel body fat estimation using machine learning and 3-dimensional optical imaging.

European journal of clinical nutrition
Estimates of body composition have been derived using 3-dimensional optical imaging (3DO), but no equations to date have been calibrated using a 4-component (4C) model criterion. This investigation reports the development of a novel body fat predicti...

Machine Learning Diagnostic Modeling for Classifying Fibromyalgia Using B-mode Ultrasound Images.

Ultrasonic imaging
Fibromyalgia (FM) diagnosis remains a challenge for clinicians due to a lack of objective diagnostic tools. One proposed solution is the use of quantitative ultrasound (US) techniques, such as image texture analysis, which has demonstrated discrimina...

Value of a Machine Learning Approach for Predicting Clinical Outcomes in Young Patients With Hypertension.

Hypertension (Dallas, Tex. : 1979)
Risk stratification of young patients with hypertension remains challenging. Generally, machine learning (ML) is considered a promising alternative to traditional methods for clinical predictions because it is capable of processing large amounts of c...