AIMC Topic: Retrospective Studies

Clear Filters Showing 3051 to 3060 of 9989 articles

Artificial intelligence predicts undiagnosed atrial fibrillation in patients with embolic stroke of undetermined source using sinus rhythm electrocardiograms.

Heart rhythm
BACKGROUND: Artificial intelligence (AI)-enabled sinus rhythm (SR) electrocardiogram (ECG) interpretation can aid in identifying undiagnosed paroxysmal atrial fibrillation (AF) in patients with embolic stroke of undetermined source (ESUS).

Machine Learning Radiomics-Based Prediction of Non-sentinel Lymph Node Metastasis in Chinese Breast Cancer Patients with 1-2 Positive Sentinel Lymph Nodes: A Multicenter Study.

Academic radiology
RATIONALE AND OBJECTIVES: This study aimed to construct a machine learning radiomics-based model using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) images to evaluate non-sentinel lymph node (NSLN) metastasis in Chinese breast cance...

Non-invasive assessment of response to transcatheter arterial chemoembolization for hepatocellular carcinoma with the deep neural networks-based radiomics nomogram.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Transcatheter arterial chemoembolization (TACE) is a mainstay treatment for intermediate and advanced hepatocellular carcinoma (HCC), with the potential to enhance patient survival. Preoperative prediction of postoperative response to TAC...

The development of a deep learning model for automated segmentation of the robotic pancreaticojejunostomy.

Surgical endoscopy
BACKGROUND: Minimally invasive surgery provides an unprecedented opportunity to review video for assessing surgical performance. Surgical video analysis is time-consuming and expensive. Deep learning provides an alternative for analysis. Robotic panc...

Assessment of Automated Identification of Phases in Videos of Total Hip Arthroplasty Using Deep Learning Techniques.

Clinics in orthopedic surgery
BACKGROUND: As the population ages, the rates of hip diseases and fragility fractures are increasing, making total hip arthroplasty (THA) one of the best methods for treating elderly patients. With the increasing number of THA surgeries and diverse s...

A novel machine-learning framework based on early embryo morphokinetics identifies a feature signature associated with blastocyst development.

Journal of ovarian research
BACKGROUND: Artificial Intelligence entails the application of computer algorithms to the huge and heterogeneous amount of morphodynamic data produced by Time-Lapse Technology. In this context, Machine Learning (ML) methods were developed in order to...

A Longitudinal Analysis of Pre- and Post-Operative Dysmorphology in Metopic Craniosynostosis.

The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association
OBJECTIVE: The purpose of this study is to objectively quantify the degree of overcorrection in our current practice and to evaluate longitudinal morphological changes using CranioRate, a novel machine learning skull morphology assessment tool.  Desi...

Multicentric development and validation of a multi-scale and multi-task deep learning model for comprehensive lower extremity alignment analysis.

Artificial intelligence in medicine
Osteoarthritis of the knee, a widespread cause of knee disability, is commonly treated in orthopedics due to its rising prevalence. Lower extremity misalignment, pivotal in knee injury etiology and management, necessitates comprehensive mechanical al...