AIMC Topic: Aged

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Prediction of posttraumatic functional recovery in middle-aged and older patients through dynamic ensemble selection modeling.

Frontiers in public health
INTRODUCTION: Age-specific risk factors may delay posttraumatic functional recovery; complex interactions exist between these factors. In this study, we investigated the prediction ability of machine learning models for posttraumatic (6 months) funct...

Artificial Intelligence-Based PTEN Loss Assessment as an Early Predictor of Prostate Cancer Metastasis After Surgery: A Multicenter Retrospective Study.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Phosphatase and tensin homolog (PTEN) loss is associated with adverse outcomes in prostate cancer and can be measured via immunohistochemistry. The purpose of the study was to establish the clinical application of an in-house developed artificial int...

Advanced age is an independent prognostic factor of disease progression in high-risk prostate cancer: results in 180 patients treated with robot-assisted radical prostatectomy and extended pelvic lymph node dissection in a tertiary referral center.

Aging clinical and experimental research
OBJECTIVES: This study aimed to assess more clinical and pathological factors associated with prostate cancer (PCa) progression in high-risk PCa patients treated primarily with robot-assisted radical prostatectomy (RARP) and extended pelvic lymph nod...

Impact of Obstructive Sleep Apnea Syndrome on Time to Complete Recovery of Continence After Robot-Assisted Radical Prostatectomy: A Propensity Score Matching Analysis.

Journal of endourology
Postoperative urinary incontinence after robot-assisted radical prostatectomy (RARP) represents a bothersome side effect, which may permanently affect patient's quality of life. Several studies have demonstrated that obstructive sleep apnea syndrome...

Human Activity Recognition Using Attention-Mechanism-Based Deep Learning Feature Combination.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) performs a vital function in various fields, including healthcare, rehabilitation, elder care, and monitoring. Researchers are using mobile sensor data (i.e., accelerometer, gyroscope) by adapting various machine lear...

Supporting SURgery with GEriatric Co-Management and AI (SURGE-Ahead): A study protocol for the development of a digital geriatrician.

PloS one
INTRODUCTION: Geriatric co-management is known to improve treatment of older adults in various clinical settings, however, widespread application of the concept is limited due to restricted resources. Digitalization may offer options to overcome thes...

Spectrochemical analysis of blood combined with chemometric techniques for detecting osteosarcopenia.

Scientific reports
Among several complications related to physiotherapy, osteosarcopenia is one of the most frequent in elderly patients. This condition is limiting and quite harmful to the patient's health by disabling several basic musculoskeletal activities. Current...

CT Angiography Radiomics Combining Traditional Risk Factors to Predict Brain Arteriovenous Malformation Rupture: a Machine Learning, Multicenter Study.

Translational stroke research
This study aimed to develop a machine learning model for predicting brain arteriovenous malformation (bAVM) rupture using a combination of traditional risk factors and radiomics features. This multicenter retrospective study enrolled 586 patients wit...

Does the Presence of Missing Data Affect the Performance of the SORG Machine-learning Algorithm for Patients With Spinal Metastasis? Development of an Internet Application Algorithm.

Clinical orthopaedics and related research
BACKGROUND: The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA) was developed to predict the survival of patients with spinal metastasis. The algorithm was successfully tested in five international institutions using 1101 patie...

Effect of Deep Learning Reconstruction on Evaluating Cervical Spinal Canal Stenosis With Computed Tomography.

Journal of computer assisted tomography
OBJECTIVE: Magnetic resonance imaging (MRI) is commonly used to evaluate cervical spinal canal stenosis; however, some patients are ineligible for MRI. We aimed to assess the effect of deep learning reconstruction (DLR) in evaluating cervical spinal ...