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Characterization of hepatocellular carcinoma with CT with deep learning reconstruction compared with iterative reconstruction and 3-Tesla MRI.
European radiology
Jan 8, 2025
OBJECTIVES: This study compared the characteristics of lesions suspicious for hepatocellular carcinoma (HCC) and their LI-RADS classifications in adaptive statistical iterative reconstruction (ASIR) and deep learning reconstruction (DLR) to those of ...
Mortality prediction after major surgery in a mixed population through machine learning: a multi-objective symbolic regression approach.
Anaesthesia
Jan 8, 2025
INTRODUCTION: Understanding 1-year mortality following major surgery offers valuable insights into patient outcomes and the quality of peri-operative care. Few models exist that predict 1-year mortality accurately. This study aimed to develop a predi...
Genomic determinants of biological age estimated by deep learning applied to retinal images.
GeroScience
Jan 8, 2025
With the development of deep learning (DL) techniques, there has been a successful application of this approach to determine biological age from latent information contained in retinal images. Retinal age gap (RAG) defined as the difference between c...
Early identification of potentially reversible cancer cachexia using explainable machine learning driven by body weight dynamics: a multicenter cohort study.
The American journal of clinical nutrition
Jan 8, 2025
BACKGROUND: Cachexia is associated with multiple adverse outcomes in cancer. However, clinical decision-making for oncology patients at the cachexia stage presents significant challenges.
AI-based models to predict decompensation on traumatic brain injury patients.
Computers in biology and medicine
Jan 8, 2025
Traumatic Brain Injury (TBI) is a form of brain injury caused by external forces, resulting in temporary or permanent impairment of brain function. Despite advancements in healthcare, TBI mortality rates can reach 30%-40% in severe cases. This study ...
CT-Based Body Composition Measures and Systemic Disease: A Population-Level Analysis Using Artificial Intelligence Tools in Over 100,000 Patients.
AJR. American journal of roentgenology
Jan 8, 2025
CT-based abdominal body composition measures have shown associations with important health outcomes. Advances in artificial intelligence (AI) now allow deployment of tools that measure body composition in large patient populations. The purpose of t...
Machine Learning to Detect Cervical Spine Fractures Missed by Radiologists on CT: Analysis Using Seven Award-Winning Models From the 2022 RSNA Cervical Spine Fracture AI Challenge.
AJR. American journal of roentgenology
Jan 8, 2025
Available data on radiologists' missed cervical spine fractures are based primarily on studies using human reviewers to identify errors on reevaluation; such studies do not capture the full extent of missed fractures. The purpose of this study was ...
Deep learning model to identify and validate hypotension endotypes in surgical and critically ill patients.
British journal of anaesthesia
Jan 8, 2025
BACKGROUND: Hypotension is associated with organ injury and death in surgical and critically ill patients. In clinical practice, treating hypotension remains challenging because it can be caused by various underlying haemodynamic alterations. We aime...
Unveiling neural activity changes in mild cognitive impairment using microstate analysis and machine learning.
Journal of Alzheimer's disease : JAD
Jan 8, 2025
BACKGROUND: Mild cognitive impairment (MCI) is recognized as a condition that may increase the risk of developing Alzheimer's disease (AD). Understanding the neural correlates of MCI is crucial for elucidating its pathophysiology and developing effec...
Artificial Intelligence Models May Aid in Predicting Lymph Node Metastasis in Patients with T1 Colorectal Cancer.
Gut and liver
Jan 8, 2025
BACKGROUND/AIMS: Inaccurate prediction of lymph node metastasis (LNM) may lead to unnecessary surgery following endoscopic resection of T1 colorectal cancer (CRC). We aimed to validate the usefulness of artificial intelligence (AI) models for predict...
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