AIMC Topic: Middle Aged

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The effect of robot-assisted walking in different modalities on cardiorespiratory responses and energy consumption in patients with subacute stroke.

Neurological research
OBJECTIVES: The aim of our study was to evaluate the effect of robot-assisted walking in different modalities on cardiorespiratory responses and energy consumption in subacute stroke patients.

Artificial intelligence-based model for lymph node metastases detection on whole slide images in bladder cancer: a retrospective, multicentre, diagnostic study.

The Lancet. Oncology
BACKGROUND: Accurate lymph node staging is important for the diagnosis and treatment of patients with bladder cancer. We aimed to develop a lymph node metastases diagnostic model (LNMDM) on whole slide images and to assess the clinical effect of an a...

Urgent Combination of Robotic and MIDCAB Coronary Revascularization in a Morbidly Obese Patient.

Innovations (Philadelphia, Pa.)
In this article, we focus on the important role of robot-assisted coronary surgery by reporting the successful case of a morbidly obese male (body mass index = 58 kg/m) who presented to our center with severe coronary disease. A 54-year-old morbidly ...

Comparison of Deep-Learning Image Reconstruction With Hybrid Iterative Reconstruction for Evaluating Lung Nodules With High-Resolution Computed Tomography.

Journal of computer assisted tomography
OBJECTIVE: This study aimed to investigate the impact of deep-learning reconstruction (DLR) on the detailed evaluation of solitary lung nodule using high-resolution computed tomography (HRCT) compared with hybrid iterative reconstruction (hybrid IR).

Deep Learning-Based Classification of Subtypes of Primary Angle-Closure Disease With Anterior Segment Optical Coherence Tomography.

Journal of glaucoma
PRCIS: We developed a deep learning-based classifier that can discriminate primary angle closure suspects (PACS), primary angle closure (PAC)/primary angle closure glaucoma (PACG), and also control eyes with open angle with acceptable accuracy.

Deep learning reconstruction with single-energy metal artifact reduction in pelvic computed tomography for patients with metal hip prostheses.

Japanese journal of radiology
PURPOSE: The aim of this study was to assess the impact of the deep learning reconstruction (DLR) with single-energy metal artifact reduction (SEMAR) (DLR-S) technique in pelvic helical computed tomography (CT) images for patients with metal hip pros...

The association of radiologic body composition parameters with clinical outcomes in level-1 trauma patients.

European journal of trauma and emergency surgery : official publication of the European Trauma Society
PURPOSE: The present study aims to assess whether CT-derived muscle mass, muscle density, and visceral fat mass are associated with in-hospital complications and clinical outcome in level-1 trauma patients.

Development and External Validation of a Machine Learning Model for Prediction of Lymph Node Metastasis in Patients with Prostate Cancer.

European urology oncology
BACKGROUND: Pelvic lymph node dissection (PLND) is the gold standard for diagnosis of lymph node involvement (LNI) in patients with prostate cancer. The Roach formula, Memorial Sloan Kettering Cancer Center (MSKCC) calculator, and Briganti 2012 nomog...

Sex determination using color fundus parameters in older adults of Kumejima population study.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: Deep learning artificial intelligence can determine the sex using only fundus photographs. However, the factors used by deep learning to determine the sex are not visible. Therefore, the purpose of the study was to determine whether the sex ...

Recalibration of a Deep Learning Model for Low-Dose Computed Tomographic Images to Inform Lung Cancer Screening Intervals.

JAMA network open
IMPORTANCE: Annual low-dose computed tomographic (LDCT) screening reduces lung cancer mortality, but harms could be reduced and cost-effectiveness improved by reusing the LDCT image in conjunction with deep learning or statistical models to identify ...