AIMC Topic: Prognosis

Clear Filters Showing 3181 to 3190 of 3837 articles

The Machine Learning Models in Major Cardiovascular Adverse Events Prediction Based on Coronary Computed Tomography Angiography: Systematic Review.

Journal of medical Internet research
BACKGROUND: Coronary computed tomography angiography (CCTA) has emerged as the first-line noninvasive imaging test for patients at high risk of coronary artery disease (CAD). When combined with machine learning (ML), it provides more valid evidence i...

Multimarker Assessment of B-Cell and Plasma Cell Subsets and Their Prognostic Role in the Colorectal Cancer Microenvironment.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Although the association between cytotoxic T lymphocytes and favorable prognosis in colorectal cancer is well established, the prognostic significance of B lymphocytes remains more ambiguous. This study aimed to assess the characteristics an...

From planning to prognosis: predicting renal function after minimally-invasive partial nephrectomy with artificial intelligence.

Minerva urology and nephrology
This study presents a machine learning model to predict renal function decline following minimally-invasive partial nephrectomy. Using a dataset of 556 patients treated between 2015 and 2023, the model incorporated patient, tumor, and intraoperative ...

A prognostic model of immunoglobulin A nephropathy using artificial neural network: a retrospective study based on integrated Chinese and Western Medicine.

Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan
OBJECTIVE: To establish and evaluate a prognostic model of immunoglobulin A nephropathy (IgAN) based on integrated Chinese and Western Medicine.

Development of a Diagnostic Prediction Model for Post-Stroke Cognitive Impairment in Acute Large Vessel Occlusion Stroke Using Multimodal MRI and PET/CT: A Study Protocol.

Brain and behavior
OBJECTIVE: Stroke is a leading cause of morbidity and disability worldwide. Post-stroke cognitive impairment (PSCI) significantly affects long-term prognosis in acute anterior circulation large-vessel occlusion stroke (LVO-AIS). This study aims to de...

Unveiling Prognostic and Diagnostic Biomarkers in Knee and Hip Osteoarthritis: A Targeted Review.

Discovery medicine
Osteoarthritis is a multifactorial condition marked by the gradual deterioration of joint cartilage, synovial inflammation, alterations in the subchondral bone and changes in the surrounding soft tissues. Clinical assessments and patient-reported out...

From Acquisition to Prognosis: The Role of AI in Cardiac Magnetic Resonance Imaging Evaluation of Ischemic Cardiomyopathy.

Echocardiography (Mount Kisco, N.Y.)
Acute and chronic ischemic cardiomyopathy (ICM) still represents a leading cause of morbidity and mortality. Cardiac magnetic resonance (CMR) imaging plays a central role in the diagnosis and management of ICM, offering detailed visualization of card...

Comparison of Sarcopenia Assessment in Liver Transplant Recipients by Computed Tomography Freehand Region-of-Interest versus an Automated Deep Learning System.

Clinical transplantation
INTRODUCTION: Sarcopenia, or the loss of muscle quality and quantity, has been associated with poor clinical outcomes in liver transplantation such as infection, increased length of stay, and increased patient mortality. Abdominal computed tomography...

Machine Learning-Assisted Analysis of the Oral Cancer Immune Microenvironment: From Single-Cell Level to Prognostic Model Construction.

Journal of cellular and molecular medicine
Oral cancer is among the most prevalent malignant tumours worldwide; prognosis can be affected by several factors, including molecular subtypes, immune microenvironment and clinical characteristics. In this study, we aimed to apply machine learning m...

Deep learning driven interpretable and informed decision making model for brain tumour prediction using explainable AI.

Scientific reports
Brain Tumours are highly complex, particularly when it comes to their initial and accurate diagnosis, as this determines patient prognosis. Conventional methods rely on MRI and CT scans and employ generic machine learning techniques, which are heavil...