AIMC Topic: Aged

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Disparities in access to robotic technology and perioperative outcomes among patients treated with radical prostatectomy.

Journal of surgical oncology
BACKGROUND: Most radical prostatectomies are completed with robotic assistance. While studies have previously evaluated perioperative outcomes of robot-assisted radical prostatectomy (RARP), this study investigates disparities in access and clinical ...

Machine and deep learning-based clinical characteristics and laboratory markers for the prediction of sarcopenia.

Chinese medical journal
BACKGROUND: Sarcopenia is an age-related progressive skeletal muscle disorder involving the loss of muscle mass or strength and physiological function. Efficient and precise AI algorithms may play a significant role in the diagnosis of sarcopenia. In...

The Impact of Fatty Infiltration on MRI Segmentation of Lower Limb Muscles in Neuromuscular Diseases: A Comparative Study of Deep Learning Approaches.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Deep learning methods have been shown to be useful for segmentation of lower limb muscle MRIs of healthy subjects but, have not been sufficiently evaluated on neuromuscular disease (NDM) patients.

Comparison of short-term outcomes and survival between minimally invasive colectomy and open colectomy in patients 80 years of age and older.

Journal of robotic surgery
We investigated the short- and long-term outcomes of patients 80 years of age and older with colon cancer who underwent robotic colectomy versus laparoscopic colectomy. Data for patients treated at a comprehensive cancer center between January 2006 a...

A Risk Prediction Model for Physical Restraints Among Older Chinese Adults in Long-term Care Facilities: Machine Learning Study.

Journal of medical Internet research
BACKGROUND: Numerous studies have identified risk factors for physical restraint (PR) use in older adults in long-term care facilities. Nevertheless, there is a lack of predictive tools to identify high-risk individuals.

Radiologist Worklist Reprioritization Using Artificial Intelligence: Impact on Report Turnaround Times for CTPA Examinations Positive for Acute Pulmonary Embolism.

AJR. American journal of roentgenology
In patients with acute pulmonary embolism (PE), timely intervention (e.g., initiation of anticoagulation) is critical for optimizing clinical outcomes. The purpose of this study was to evaluate the effect of artificial intelligence (AI)-based radio...

And then there was one … incision. First single-port pediatric robotic case series.

Journal of pediatric urology
BACKGROUND: In the past two decades, technology has advanced to augment an already minimally-invasive approach in laparoscopic surgery. Robotic-assisted laparoscopic platforms have now evolved to its 4th-generation product: a single-port system, firs...

Stratified assessment of an FDA-cleared deep learning algorithm for automated detection and contouring of metastatic brain tumors in stereotactic radiosurgery.

Radiation oncology (London, England)
PURPOSE: Artificial intelligence-based tools can be leveraged to improve detection and segmentation of brain metastases for stereotactic radiosurgery (SRS). VBrain by Vysioneer Inc. is a deep learning algorithm with recent FDA clearance to assist in ...

Remote assessment of cognition and quality of life following radiotherapy for glioma: deep-learning-based predictive models and MRI correlates.

Journal of neuro-oncology
BACKGROUND: Glioma irradiation often unavoidably damages the brain volume and affects cognition. This study aims to evaluate the relationship of remote cognitive assessments in determining cognitive impairment of irradiated glioma patients in relatio...

Remote assessment of cognition and quality of life following radiotherapy for nasopharyngeal carcinoma: deep-learning-based predictive models and MRI correlates.

Journal of cancer survivorship : research and practice
PURPOSE: Irradiation of the brain regions from nasopharyngeal carcinoma (NPC) radiotherapy (RT) is frequently unavoidable, which may result in radiation-induced cognitive deficit. Using deep learning (DL), the study aims to develop prediction models ...