AIMC Topic: Middle Aged

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Prediction of systemic biomarkers from retinal photographs: development and validation of deep-learning algorithms.

The Lancet. Digital health
BACKGROUND: The application of deep learning to retinal photographs has yielded promising results in predicting age, sex, blood pressure, and haematological parameters. However, the broader applicability of retinal photograph-based deep learning for ...

Use of Natural Language Processing to Assess Frequency of Functional Status Documentation for Patients Newly Diagnosed With Colorectal Cancer.

JAMA oncology
This cross-sectional study applies natural language processing to electronic health records from a large health care delivery system to examine performance status documentation among patients newly diagnosed with colorectal cancer.

External Evaluation of 3 Commercial Artificial Intelligence Algorithms for Independent Assessment of Screening Mammograms.

JAMA oncology
IMPORTANCE: A computer algorithm that performs at or above the level of radiologists in mammography screening assessment could improve the effectiveness of breast cancer screening.

A statistically rigorous deep neural network approach to predict mortality in trauma patients admitted to the intensive care unit.

The journal of trauma and acute care surgery
BACKGROUND: Trauma patients admitted to critical care are at high risk of mortality because of their injuries. Our aim was to develop a machine learning-based model to predict mortality using Fahad-Liaqat-Ahmad Intensive Machine (FLAIM) framework. We...

Large-Scale Structural Covariance Networks Predict Age in Middle-to-Late Adulthood: A Novel Brain Aging Biomarker.

Cerebral cortex (New York, N.Y. : 1991)
The aging process is accompanied by changes in the brain's cortex at many levels. There is growing interest in summarizing these complex brain-aging profiles into a single, quantitative index that could serve as a biomarker both for characterizing in...

Evaluating the Sensitivity of Resting-State BOLD Variability to Age and Cognition after Controlling for Motion and Cardiovascular Influences: A Network-Based Approach.

Cerebral cortex (New York, N.Y. : 1991)
Recent functional magnetic resonance imaging (fMRI) studies report that moment-to-moment variability in the BOLD signal is related to differences in age and cognition and, thus, may be sensitive to age-dependent decline. However, head motion and/or c...

Feasibility of machine learning based predictive modelling of postoperative hyponatremia after pituitary surgery.

Pituitary
PURPOSE: Hyponatremia after pituitary surgery is a frequent finding with potential severe complications and the most common cause for readmission. Several studies have found parameters associated with postoperative hyponatremia, but no reliable speci...

How Does the Skeletal Oncology Research Group Algorithm's Prediction of 5-year Survival in Patients with Chondrosarcoma Perform on International Validation?

Clinical orthopaedics and related research
BACKGROUND: The Skeletal Oncology Research Group (SORG) machine learning algorithm for predicting survival in patients with chondrosarcoma was developed using data from the Surveillance, Epidemiology, and End Results (SEER) registry. This algorithm w...