AIMC Topic: Retrospective Studies

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Deep learning-based model for difficult transfemoral access prediction compared with human assessment in stroke thrombectomy.

Journal of neurointerventional surgery
BACKGROUND: In mechanical thrombectomy (MT), extracranial vascular tortuosity is among the main determinants of procedure duration and success. Currently, no rapid and reliable method exists to identify the anatomical features precluding fast and sta...

Serum calcium-based interpretable machine learning model for predicting anastomotic leakage after rectal cancer resection: A multi-center study.

World journal of gastroenterology
BACKGROUND: Despite the promising prospects of utilizing artificial intelligence and machine learning (ML) for comprehensive disease analysis, few models constructed have been applied in clinical practice due to their complexity and the lack of reaso...

Characterization of subepithelial tumors of upper gastrointestinal tract by endoscopic ultrasound.

World journal of gastroenterology
In this article we comment on the paper by Xu describing retrospective data on endoscopic treatment outcome of esophageal gastrointestinal stromal tumors (GISTs). Esophageal GIST is a rare type of mesenchymal tumor. GISTs originate from the intersti...

A machine learning based prediction model for short term efficacy of nasopharyngeal carcinoma.

Scientific reports
The radiological dosimetric parameters and clinical features were screened by machine learning to construct a prediction model for the short-term efficacy of locally advanced Nasopharyngeal Carcinoma (LANPC). Patients diagnosed with Nasopharyngeal Ca...

Prediction of Spontaneous Breathing Trial Outcome in Critically Ill-Ventilated Patients Using Deep Learning: Development and Verification Study.

JMIR medical informatics
BACKGROUND: Long-term ventilator-dependent patients often face problems such as decreased quality of life, increased mortality, and increased medical costs. Respiratory therapists must perform complex and time-consuming ventilator weaning assessments...

Optimizing influenza vaccine allocation: A predictive analytics approach for informed public health planning.

American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists
PURPOSE: Excessive purchasing of influenza vaccine can lead to costly overages and waste of resources. Insufficient quantities, however, can jeopardize population health. Our project aimed to use predictive analytics to determine the influenza vaccin...

Evaluating Prevalence of Preterm Postnatal Growth Faltering Using Fenton 2013 and INTERGROWTH-21st Growth Charts with Logistic and Machine Learning Models.

Nutrients
Postnatal growth faltering (PGF) significantly affects premature neonates, leading to compromised neurodevelopment and an increased risk of long-term health complications. This retrospective study at a level III NICU of a tertiary hospital analyzed...

Understanding Transient Left Ventricular Ejection Fraction Reduction During Atrial Fibrillation With Artificial Intelligence.

Journal of the American Heart Association
BACKGROUND: Atrial fibrillation (AF) can cause a reduction in left ventricular ejection fraction (LVEF) that resolves rapidly upon restoration of sinus rhythm. We used artificial intelligence to understand (1) how often transient LVEF reduction durin...

Deep learning models based on multiparametric magnetic resonance imaging and clinical parameters for identifying synchronous liver metastases from rectal cancer.

BMC medical imaging
OBJECTIVES: To establish and validate deep learning (DL) models based on pre-treatment multiparametric magnetic resonance imaging (MRI) images of primary rectal cancer and basic clinical data for the prediction of synchronous liver metastases (SLM) i...

Assessing artificial intelligence ability in predicting hospitalization duration for pleural empyema patients managed with uniportal video-assisted thoracoscopic surgery: a retrospective observational study.

BMC surgery
BACKGROUND: This retrospective observational research evaluates the potential applicability of artificial intelligence models to predict the length of hospital stay for patients with pleural empyema who underwent uniportal video-assisted thoracoscopi...