AIMC Topic: Aged

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Effect of robot for medication management on home care professionals' use of working time in older people's home care: a non-randomized controlled clinical trial.

BMC health services research
BACKGROUND: Medication management has a key role in the daily tasks of home care professionals delivered to older clients in home care. The aim of this study was to examine the effect of using a robot for medication management on home care profession...

Achalasia phenotypes and prediction of peroral endoscopic myotomy outcomes using machine learning.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
OBJECTIVES: High-resolution manometry (HRM) and esophagography are used for achalasia diagnosis; however, achalasia phenotypes combining esophageal motility and morphology are unknown. Moreover, predicting treatment outcomes of peroral endoscopic myo...

Predicting incomplete occlusion of intracranial aneurysms treated with flow diverters using machine learning models.

Journal of neurosurgery
OBJECTIVE: Intracranial saccular aneurysms are vascular malformations responsible for 80% of nontraumatic brain hemorrhage. Recently, flow diverters have been used as a less invasive therapeutic alternative for surgery. However, they fail to achieve ...

Machine Learning Model with Computed Tomography Radiomics and Clinicobiochemical Characteristics Predict the Subtypes of Patients with Primary Aldosteronism.

Academic radiology
RATIONALE AND OBJECTIVES: Adrenal venous sampling (AVS) is the primary method for differentiating between primary aldosterone (PA) subtypes. The aim of study is to develop prediction models for subtyping of patients with PA using computed tomography ...

Comparison of Ultrasound-Guided Anterior, Posterior and Combination of Quadratus Lumborum Block in Laparoscopic Abdominal Surgeries: A Pilot Study.

Asian journal of anesthesiology
BACKGROUND: The quadratus lumborum block (QLB) is an effective technique to provide analgesia for upper and lower abdominal surgeries. There are various approaches described in the literature, but the best approach is still to be explored. This study...

Interpretable machine learning-based predictive modeling of patient outcomes following cardiac surgery.

The Journal of thoracic and cardiovascular surgery
BACKGROUND: The clinical applicability of machine learning predictions of patient outcomes following cardiac surgery remains unclear. We applied machine learning to predict patient outcomes associated with high morbidity and mortality after cardiac s...

Glioma Tumor Grading Using Radiomics on Conventional MRI: A Comparative Study of WHO 2021 and WHO 2016 Classification of Central Nervous Tumors.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Glioma grading transformed in World Health Organization (WHO) 2021 CNS tumor classification, integrating molecular markers. However, the impact of this change on radiomics-based machine learning (ML) classifiers remains unexplored.

A multimodal screening system for elderly neurological diseases based on deep learning.

Scientific reports
In this paper, we propose a deep-learning-based algorithm for screening neurological diseases. We proposed various examination protocols for screening neurological diseases and collected data by video-recording persons performing these protocols. We ...

Machine Learning Web Application for Predicting Functional Outcomes in Patients With Traumatic Spinal Cord Injury Following Inpatient Rehabilitation.

Journal of neurotrauma
Accurately predicting functional outcomes in patients with spinal cord injury (SCI) helps clinicians set realistic functional recovery goals and improve the home environment after discharge. The present study aimed to develop and validate machine lea...