AIMC Topic: Retrospective Studies

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Artificial intelligence methods to estimate overall mortality and non-relapse mortality following allogeneic HCT in the modern era: an EBMT-TCWP study.

Bone marrow transplantation
Allogeneic haematopoietic cell transplantation (alloHCT) has curative potential counterbalanced by its toxicity. Prognostic scores fail to include current era patients and alternative donors. We examined adult patients from the EBMT registry who unde...

CT analysis of aortic calcifications to predict abdominal aortic aneurysm rupture.

European radiology
BACKGROUND: Abdominal aortic aneurysm (AAA) rupture prediction based on sex and diameter could be improved. The goal was to assess whether aortic calcification distribution could better predict AAA rupture through machine learning and LASSO regressio...

Prognostication of Outcomes in Spontaneous Intracerebral Hemorrhage: A Propensity Score-Matched Analysis with Support Vector Machine.

World neurosurgery
OBJECTIVE: The role of surgery in spontaneous intracerebral hemorrhage (SICH) remains controversial. We aimed to use explainable machine learning (ML) combined with propensity-score matching to investigate the effects of surgery and identify subgroup...

Implications of ultrasound-based deep learning model for preoperatively differentiating combined hepatocellular-cholangiocarcinoma from hepatocellular carcinoma and intrahepatic cholangiocarcinoma.

Abdominal radiology (New York)
OBJECTIVES: The current study developed an ultrasound-based deep learning model to make preoperative differentiation among hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC), and combined hepatocellular-cholangiocarcinoma (cHCC-ICC...

A Lightweight Deep Learning Framework for Automatic MRI Data Sorting and Artifacts Detection.

Journal of medical systems
The purpose of this study is to develop a lightweight and easily deployable deep learning system for fully automated content-based brain MRI sorting and artifacts detection. 22092 MRI volumes from 4076 patients between 2017 and 2021 were involved in ...

Outcomes Comparison of Robot-Assisted and Video-Assisted Thoracoscopic Cardiac Sympathetic Denervation.

Innovations (Philadelphia, Pa.)
OBJECTIVE: Cardiac sympathetic denervation (CSD) is a surgical antiadrenergic procedure that can reduce sustained ventricular tachyarrhythmia (VT). Video-assisted thoracoscopic surgery (VATS) is currently the standard approach used in CSD, and the pr...

Automatic image segmentation and online survival prediction model of medulloblastoma based on machine learning.

European radiology
OBJECTIVES: To develop a dynamic nomogram containing radiomics signature and clinical features for estimating the overall survival (OS) of patients with medulloblastoma (MB) and design an automatic image segmentation model to reduce labor and time co...

Deep-Learning Automation of Preoperative Radiographic Parameters Associated With Early Periprosthetic Femur Fracture After Total Hip Arthroplasty.

The Journal of arthroplasty
BACKGROUND: The radiographic assessment of bone morphology impacts implant selection and fixation type in total hip arthroplasty (THA) and is important to minimize the risk of periprosthetic femur fracture (PFF). We utilized a deep-learning algorithm...

Deep learning approaches for differentiating thyroid nodules with calcification: a two-center study.

BMC cancer
BACKGROUND: Calcification is a common phenomenon in both benign and malignant thyroid nodules. However, the clinical significance of calcification remains unclear. Therefore, we explored a more objective method for distinguishing between benign and m...

Saliency of breast lesions in breast cancer detection using artificial intelligence.

Scientific reports
The analysis of mammograms using artificial intelligence (AI) has shown great potential for assisting breast cancer screening. We use saliency maps to study the role of breast lesions in the decision-making process of AI systems for breast cancer det...