AIMC Topic: Middle Aged

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A Systematic Analysis of 3D Deformation of Aging Breasts Based on Artificial Neural Networks.

International journal of environmental research and public health
The measurement and prediction of breast skin deformation are key research directions in health-related research areas, such as cosmetic and reconstructive surgery and sports biomechanics. However, few studies have provided a systematic analysis on t...

Automated estimation of ischemic core volume on noncontrast-enhanced CT via machine learning.

Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences
BACKGROUND: Accurate estimation of ischemic core on baseline imaging has treatment implications in patients with acute ischemic stroke (AIS). Machine learning (ML) algorithms have shown promising results in estimating ischemic core using routine nonc...

Development and validation of a machine learning algorithm for predicting diffuse midline glioma, H3 K27-altered, H3 K27 wild-type high-grade glioma, and primary CNS lymphoma of the brain midline in adults.

Journal of neurosurgery
OBJECTIVE: Preoperative diagnosis of diffuse midline glioma, H3 K27-altered (DMG-A) and midline high-grade glioma without H3 K27 alteration (DMG-W), as well as midline primary CNS lymphoma (PCNSL) in adults, is challenging but crucial. The aim of thi...

Assess the documentation of cognitive tests and biomarkers in electronic health records via natural language processing for Alzheimer's disease and related dementias.

International journal of medical informatics
BACKGROUND: Cognitive tests and biomarkers are the key information to assess the severity and track the progression of Alzheimer's' disease (AD) and AD-related dementias (AD/ADRD), yet, both are often only documented in clinical narratives of patient...

Deep learning-based assessment of body composition and liver tumour burden for survival modelling in advanced colorectal cancer.

Journal of cachexia, sarcopenia and muscle
BACKGROUND: Personalized therapy planning remains a significant challenge in advanced colorectal cancer care, despite extensive research on prognostic and predictive markers. A strong correlation of sarcopenia or overall body composition and survival...

Acute Intraoperative Hyperkalemia During Robot-Assisted Radical Cystectomy: A Case Report.

A&A practice
A 50-year-old man with muscle-invasive bladder cancer was scheduled for a robotic radical cystectomy. Four hours into the surgery, his electrocardiogram showed rhythm disturbances. Arterial blood gas analysis showed a serum potassium concentration of...

Role of deep learning methods in screening for subcutaneous implantable cardioverter defibrillator in heart failure.

Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc
INTRODUCTION: S-ICD eligibility is assessed at pre-implant screening where surface ECG traces are used as surrogates for S-ICD vectors. In heart failure (HF) patients undergoing diuresis, electrolytes and fluid shifts can cause changes in R and T wav...

Artificial Intelligence-based CT Assessment of Bronchiectasis: The COPDGene Study.

Radiology
Background CT is the standard method used to assess bronchiectasis. A higher airway-to-artery diameter ratio (AAR) is typically used to identify enlarged bronchi and bronchiectasis; however, current imaging methods are limited in assessing the extent...

A Machine Learning Model for Prediction of Amputation in Diabetics.

Journal of diabetes science and technology
BACKGROUND: Diabetic foot ulcer (DFU) and the resulting lower extremity amputation are associated with a poor survival prognosis. The objective of this study is to generate a model for predicting the probability of major amputation in hospitalized pa...

Neurosurgery inpatient outcome prediction for discharge planning with deep learning and transfer learning.

British journal of neurosurgery
INTRODUCTION: Deep learning may be able to assist with the prediction of neurosurgical inpatient outcomes. The aims of this study were to investigate deep learning and transfer learning in the prediction of several inpatient outcomes including timing...