AIMC Topic: Adult

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[Construction of a back propagation neural network model for predicting urosepsis after flexible ureteroscopic lithotripsy].

Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences
OBJECTIVES: To analyze the association of serum heparin-binding protein (HBP) and C-reactive protein (CRP) levels with urosepsis following flexible ureteroscopic lithotripsy (FURL) and to construct a back propagation neural network prediction model.

Sex estimation based on mandibular measurements.

Anthropologischer Anzeiger; Bericht uber die biologisch-anthropologische Literatur
Medical imaging and machine learning are beneficial approaches in physical and forensic anthropology. They are particularly useful for the development of models for sex identification based on bone remains. The present study uses machine learning alg...

Machine learning assessment of dental age classification based on cone-beam CT images: a different approach.

Dento maxillo facial radiology
OBJECTIVES: Machine learning (ML) algorithms are a portion of artificial intelligence that may be used to create more accurate algorithmic procedures for estimating an individual's dental age or defining an age classification. This study aims to use ...

Stratum corneum nanotexture feature detection using deep learning and spatial analysis: a noninvasive tool for skin barrier assessment.

GigaScience
BACKGROUND: Corneocyte surface nanoscale topography (nanotexture) has recently emerged as a potential biomarker for inflammatory skin diseases, such as atopic dermatitis (AD). This assessment method involves quantifying circular nano-size objects (CN...

Artificial intelligence-assisted quantification and assessment of whole slide images for pediatric kidney disease diagnosis.

Bioinformatics (Oxford, England)
MOTIVATION: Pediatric kidney disease is a widespread, progressive condition that severely impacts growth and development of children. Chronic kidney disease is often more insidious in children than in adults, usually requiring a renal biopsy for diag...

Federated Diabetes Prediction in Canadian Adults Using Real-world Cross-Province Primary Care Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Integrating Electronic Health Records (EHR) and the application of machine learning present opportunities for enhancing the accuracy and accessibility of data-driven diabetes prediction. In particular, developing data-driven machine learning models c...

Deep Learning-based Time-to-event Analysis of Depression and Asthma using the All of Us Research Program.

AMIA ... Annual Symposium proceedings. AMIA Symposium
While there is a growing recognition of the association between depression and asthma, few studies have leveraged deep learning-based (DL-based) models in a retrospective cohort study with a large sample size. We analyzed the association between depr...

Process optimisation: spinal versus general anaesthesia for endourological surgery. A randomised, controlled trial and machine-learning approach.

Anaesthesiology intensive therapy
INTRODUCTION: Data concerning anaesthesia for endourology are rare, and options for it are numerous. Thus, identifying the optimal anaesthesia regimen remains challenging. With this study we aimed to provide the means for selecting optimal anaesthesi...

The Added Effect of Artificial Intelligence in CT Assessment of Abdominal Lymphadenopathy.

Lymphology
Lymphadenopathy is associated with lymph node abnormal size or consistency due to many causes. We employed the deep convolutional neural network ResNet-34 to detect and classify CT images from patients with abdominal lymphadenopathy and healthy contr...