AIMC Topic: Aged

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Diagnosis and Treatment Effect of Convolutional Neural Network-Based Magnetic Resonance Image Features on Severe Stroke and Mental State.

Contrast media & molecular imaging
The purpose of this paper is to explore the impact of magnetic resonance imaging (MRI) image features based on convolutional neural network (CNN) algorithm and conditional random field on the diagnosis and mental state of patients with severe stroke....

Magnetic Resonance Imaging Features of Cerebral Infarction in Critical Patients Based on Convolutional Neural Network.

Contrast media & molecular imaging
The clinical application of the artificial intelligence-assisted system in imaging was investigated by analyzing the magnetic resonance imaging (MRI) influence characteristics of cerebral infarction in critically ill patients based on the convolution...

Machine learning analysis of multispectral imaging and clinical risk factors to predict amputation wound healing.

Journal of vascular surgery
OBJECTIVE: Prediction of amputation wound healing is challenging due to the multifactorial nature of critical limb ischemia and lack of objective assessment tools. Up to one-third of amputations require revision to a more proximal level within 1 year...

Intermediate-term survival of robot-assisted versus open radical cystectomy for muscle-invasive and high-risk non-muscle invasive bladder cancer in The Netherlands.

Urologic oncology
BACKGROUND: Radical cystectomy with pelvic lymph node dissection is the recommended treatment in non-metastatic muscle-invasive bladder cancer (MIBC). In randomised trials, robot-assisted radical cystectomy (RARC) showed non-inferior short-term oncol...

Artificial Intelligence-Enabled ECG to Identify Silent Atrial Fibrillation in Embolic Stroke of Unknown Source.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: Embolic strokes of unknown source (ESUS) are common and often suspected to be caused by unrecognized paroxysmal atrial fibrillation (AF). An AI-enabled ECG (AI-ECG) during sinus rhythm has been shown to identify patients with unrecognized...

Prediction model for malignant pulmonary nodules based on cfMeDIP-seq and machine learning.

Cancer science
Cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) is a new bisulfite-free technique, which can detect the whole-genome methylation of blood cell-free DNA (cfDNA). Using this technique, we identified differentia...

Automated cortical thickness measurement of the mandibular condyle head on CBCT images using a deep learning method.

Scientific reports
This study proposes a deep learning model for cortical bone segmentation in the mandibular condyle head using cone-beam computed tomography (CBCT) and an automated method for measuring cortical thickness with a color display based on the segmentation...

Survival prognostic factors in patients with acute myeloid leukemia using machine learning techniques.

PloS one
This paper identifies prognosis factors for survival in patients with acute myeloid leukemia (AML) using machine learning techniques. We have integrated machine learning with feature selection methods and have compared their performances to identify ...

Cost-effectiveness of artificial intelligence monitoring for active tuberculosis treatment: A modeling study.

PloS one
BACKGROUND: Tuberculosis (TB) incidence in Los Angeles County, California, USA (5.7 per 100,000) is significantly higher than the U.S. national average (2.9 per 100,000). Directly observed therapy (DOT) is the preferred strategy for active TB treatme...

Deep learning approach to predict sentinel lymph node status directly from routine histology of primary melanoma tumours.

European journal of cancer (Oxford, England : 1990)
AIM: Sentinel lymph node status is a central prognostic factor for melanomas. However, the surgical excision involves some risks for affected patients. In this study, we therefore aimed to develop a digital biomarker that can predict lymph node metas...