AIMC Topic: Aged, 80 and over

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Utilization of Minimally Invasive Thymectomy and Margin-Negative Resection for Early-Stage Thymoma.

The Annals of thoracic surgery
BACKGROUND: Minimally invasive thymectomy (MIT) has demonstrated improved short-term outcomes compared with open thymectomy (OT). Although adoption of MIT for thymoma is increasing, oncologic outcomes have not been well characterized.

Artificial intelligence detection of distal radius fractures: a comparison between the convolutional neural network and professional assessments.

Acta orthopaedica
Background and purpose - Artificial intelligence has rapidly become a powerful method in image analysis with the use of convolutional neural networks (CNNs). We assessed the ability of a CNN, with a fast object detection algorithm previously identify...

Diagnostic accuracy of frontotemporal dementia. An artificial intelligence-powered study of symptoms, imaging and clinical judgement.

Advances in medical sciences
PURPOSE: Frontotemporal dementia (FTD) is a neurodegenerative disorder associated with a poor prognosis and a substantial reduction in quality of life. The rate of misdiagnosis of FTD is very high, with patients often waiting for years without a firm...

Application of a deep learning algorithm for detection and visualization of hip fractures on plain pelvic radiographs.

European radiology
OBJECTIVE: To identify the feasibility of using a deep convolutional neural network (DCNN) for the detection and localization of hip fractures on plain frontal pelvic radiographs (PXRs). Hip fracture is a leading worldwide health problem for the elde...

Deep learning for identifying environmental risk factors of acute respiratory diseases in Beijing, China: implications for population with different age and gender.

International journal of environmental health research
This study focuses on identifying environmental health risk factors related to acute respiratory diseases using deep learning method. Based on respiratory disease data, air pollution data and meteorological environmental data, cross-domain risk facto...

Feature-weighted survival learning machine for COPD failure prediction.

Artificial intelligence in medicine
Chronic obstructive pulmonary disease (COPD) yields a high rate of failures such as hospital readmission and death in the United States, Canada and worldwide. COPD failure imposes a significant social and economic burden on society, and predicting su...

Falls Risk Classification of Older Adults Using Deep Neural Networks and Transfer Learning.

IEEE journal of biomedical and health informatics
Prior research in falls risk classification using inertial sensors has relied on the use of engineered features, which has resulted in a feature space containing hundreds of features that are likely redundant and possibly irrelevant. In this paper, w...

Evaluation of a sensor algorithm for motor state rating in Parkinson's disease.

Parkinsonism & related disorders
INTRODUCTION: A treatment response objective index (TRIS) was previously developed based on sensor data from pronation-supination tests. This study aimed to examine the performance of TRIS for medication effects in a new population sample with Parkin...

Automated tumour budding quantification by machine learning augments TNM staging in muscle-invasive bladder cancer prognosis.

Scientific reports
Tumour budding has been described as an independent prognostic feature in several tumour types. We report for the first time the relationship between tumour budding and survival evaluated in patients with muscle invasive bladder cancer. A machine lea...

Can We Accurately Identify Peritoneal Metastases Based on Their Appearance? An Assessment of the Current Practice of Intraoperative Gastrointestinal Cancer Staging.

Annals of surgical oncology
BACKGROUND: Peritoneal lesions are common findings during operative abdominal cancer staging. The decision to perform biopsy is made subjectively by the surgeon, a practice the authors hypothesized to be imprecise. This study aimed to describe optica...