Prostate age gap: An MRI surrogate marker of aging for prostate cancer detection
A Fernandez‐Quilez, T Nordström… - Journal of Magnetic …, 2023 - Wiley Online Library
Background Aging is the most important risk factor for prostate cancer (PC). Imaging
techniques can be useful to measure age‐related changes associated with the transition to …
techniques can be useful to measure age‐related changes associated with the transition to …
[HTML][HTML] Deep learning-based age estimation from clinical Computed Tomography image data of the thorax and abdomen in the adult population
Aging is an important risk factor for disease, leading to morphological change that can be
assessed on Computed Tomography (CT) scans. We propose a deep learning model for …
assessed on Computed Tomography (CT) scans. We propose a deep learning model for …
AI analysis of chest radiographs as a biomarker of biological age
PS Babyn, SJ Adams - The Lancet Healthy Longevity, 2023 - thelancet.com
Chronological age is the greatest risk factor for most common chronic diseases. However,
molecular and cellular age-related decline varies substantively between individuals …
molecular and cellular age-related decline varies substantively between individuals …
Deep Regression for Biological Age Estimation in Multiple Organs: Investigations on 40,000 Subjects of the UK Biobank
Age plays an important role in shaping medical decisions, but the biological changes
associated with aging do not solely depend on the chronological age. Genetics, lifestyle …
associated with aging do not solely depend on the chronological age. Genetics, lifestyle …
AI Age Discrepancy: A Novel Parameter for Frailty Assessment in Kidney Tumor Patients
J Siva, A Bartholomew, C Goebel… - arXiv preprint arXiv …, 2024 - arxiv.org
Kidney cancer is a global health concern, and accurate assessment of patient frailty is
crucial for optimizing surgical outcomes. This paper introduces AI Age Discrepancy, a novel …
crucial for optimizing surgical outcomes. This paper introduces AI Age Discrepancy, a novel …
Lung age estimation from low-dose chest CT images using deep learning
H Kikuno, R Tanaka, S Kobayashi… - Medical Imaging …, 2024 - spiedigitallibrary.org
Purpose: To develop a deep learning model to estimate lung age based on low-dose chest
computed tomography (CT) images and investigate the feasibility of its application in health …
computed tomography (CT) images and investigate the feasibility of its application in health …