AIMC Topic: Prognosis

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Development and validation of a machine learning-based prediction model for hepatorenal syndrome in liver cirrhosis patients using MIMIC-IV and eICU databases.

Scientific reports
Hepatorenal syndrome (HRS) is a key contributor to poor prognosis in liver cirrhosis. This study aims to leverage the database to build a predictive model for early identification of high-risk patients. From two sizable public databases, we retrieved...

PEDRA-EFB0: colorectal cancer prognostication using deep learning with patch embeddings and dual residual attention.

Medical & biological engineering & computing
In computer-aided diagnosis systems, precise feature extraction from CT scans of colorectal cancer using deep learning is essential for effective prognosis. However, existing convolutional neural networks struggle to capture long-range dependencies a...

Artificial intelligence-enhanced comprehensive assessment of the aortic valve stenosis continuum in echocardiography.

EBioMedicine
BACKGROUND: Transthoracic echocardiography (TTE) is the primary modality for diagnosing aortic stenosis (AS), yet it requires skilled operators and can be resource-intensive. We developed and validated an artificial intelligence (AI)-based system for...

Comparative analysis of deep learning and radiomic signatures for overall survival prediction in recurrent high-grade glioma treated with immunotherapy.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Radiomic analysis of quantitative features extracted from segmented medical images can be used for predictive modeling of prognosis in brain tumor patients. Manual segmentation of the tumor components is time-consuming and poses significa...

Machine learning based prediction models for the prognosis of COVID-19 patients with DKA.

Scientific reports
Patients with Diabetic ketoacidosis (DKA) have increased critical illness and mortality during coronavirus diseases 2019 (COVID-19). The aim of our study was to develop a predictive model for the occurrence of critical illness and mortality in COVID-...

Development of metastasis and survival prediction model of luminal and non-luminal breast cancer with weakly supervised learning based on pathomics.

PeerJ
OBJECTIVE: Breast cancer stands as the most prevalent form of cancer among women globally. This heterogeneous disease exhibits varying clinical behaviors. The stratification of breast cancer patients into risk groups, determined by their metastasis a...

Deep Learning-Enabled Assessment of Right Ventricular Function Improves Prognostication After Transcatheter Edge-to-Edge Repair for Mitral Regurgitation.

Circulation. Cardiovascular imaging
BACKGROUND: Right ventricular (RV) function has a well-established prognostic role in patients with severe mitral regurgitation (MR) undergoing transcatheter edge-to-edge repair (TEER) and is typically assessed using echocardiography-measured tricusp...

Interpretable machine learning model for outcome prediction in patients with aneurysmatic subarachnoid hemorrhage.

Critical care (London, England)
BACKGROUND: Aneurysmatic subarachnoid hemorrhage (aSAH) is a critical condition associated with significant mortality rates and complex rehabilitation challenges. Early prediction of functional outcomes is essential for optimizing treatment strategie...