AIMC Topic: Female

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The Use of Artificial Neural Network to Predict Surgical Outcomes After Inguinal Hernia Repair.

The Journal of surgical research
BACKGROUND: Inguinal hernia repair is one of the most commonly performed surgical procedures. We developed and validated an artificial neural network (ANN) model for the prediction of surgical outcomes and the analysis of risk factors for inguinal he...

Central Reading of Ulcerative Colitis Clinical Trial Videos Using Neural Networks.

Gastroenterology
BACKGROUND AND AIMS: Endoscopic disease activity scoring in ulcerative colitis (UC) is useful in clinical practice but done infrequently. It is required in clinical trials, where it is expensive and slow because human central readers are needed. A ma...

Predicting brain age with complex networks: From adolescence to adulthood.

NeuroImage
In recent years, several studies have demonstrated that machine learning and deep learning systems can be very useful to accurately predict brain age. In this work, we propose a novel approach based on complex networks using 1016 T1-weighted MRI brai...

[Leptin sexual dimorphism, insulin resistance, and body composition in normal weight prepubescent].

Revista chilena de pediatria
INTRODUCTION: The prepubertal stage is a critical period of body fat development, in which leptin and insulin re sistance has been associated, however, there are few studies in normal-weight prepubescents. Ob jective: To assess the relationship betwe...

Machine Learning Algorithms for the Prediction of Central Lymph Node Metastasis in Patients With Papillary Thyroid Cancer.

Frontiers in endocrinology
BACKGROUND: Central lymph node metastasis (CLNM) occurs frequently in patients with papillary thyroid cancer (PTC), but performing prophylactic central lymph node dissection is still controversial. There are no reliable models for predicting CLNM. Th...

Telerobotic ultrasound to provide obstetrical ultrasound services remotely during the COVID-19 pandemic.

Journal of telemedicine and telecare
INTRODUCTION: Obstetrical ultrasound imaging is critical in identifying at-risk pregnancies and informing clinical management. The coronavirus disease 2019 (COVID-19) pandemic has exacerbated challenges in accessing obstetrical ultrasound for patient...

Elastic Registration-driven Deep Learning for Longitudinal Assessment of Systemic Sclerosis Interstitial Lung Disease at CT.

Radiology
Background Longitudinal follow-up of interstitial lung diseases (ILDs) at CT mainly relies on the evaluation of the extent of ILD, without accounting for lung shrinkage. Purpose To develop a deep learning-based method to depict worsening of ILD based...

Artificial Intelligence Applied to Breast MRI for Improved Diagnosis.

Radiology
Background Recognition of salient MRI morphologic and kinetic features of various malignant tumor subtypes and benign diseases, either visually or with artificial intelligence (AI), allows radiologists to improve diagnoses that may improve patient tr...

Breast ultrasound lesion classification based on image decomposition and transfer learning.

Medical physics
PURPOSE: In medical image analysis, deep learning has great application potential. Discovering a method for extracting valuable information from medical images and integrating that information closely with medical treatment has recently become a majo...