AIMC Topic: Middle Aged

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Multimodal Assessment of Parkinson's Disease: A Deep Learning Approach.

IEEE journal of biomedical and health informatics
Parkinson's disease is a neurodegenerative disorder characterized by a variety of motor symptoms. Particularly, difficulties to start/stop movements have been observed in patients. From a technical/diagnostic point of view, these movement changes can...

Predictors of atrial fibrillation early recurrence following cryoballoon ablation of pulmonary veins using statistical assessment and machine learning algorithms.

Heart and vessels
Inflammation, oxidative stress, myocardial injury biomarkers and clinical parameters (longer AF duration, left atrial enlargement, the metabolic syndrome) are factors commonly related to AF recurrence. This study aims to assess the predictive value o...

Convolutional Neural Network Using a Breast MRI Tumor Dataset Can Predict Oncotype Dx Recurrence Score.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Oncotype Dx is a validated genetic analysis that provides a recurrence score (RS) to quantitatively predict outcomes in patients who meet the criteria of estrogen receptor positive / human epidermal growth factor receptor-2 negative (ER+/...

Minimally invasive donor nephrectomy: current state of the art.

Langenbeck's archives of surgery
BACKGROUND: The concept of a minimally invasive live donor nephrectomy developed over 20 years ago. Surgeons gained expertise with the laparoscopic technique and utilized multiple variations that are now utilized in transplant centers throughout the ...

Improvement of Adequate Digoxin Dosage: An Application of Machine Learning Approach.

Journal of healthcare engineering
Digoxin is a high-alert medication because of its narrow therapeutic range and high drug-to-drug interactions (DDIs). Approximately 50% of digoxin toxicity cases are preventable, which motivated us to improve the treatment outcomes of digoxin. The ob...

Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data.

NeuroImage
A large number of papers have introduced novel machine learning and feature extraction methods for automatic classification of Alzheimer's disease (AD). However, while the vast majority of these works use the public dataset ADNI for evaluation, they ...

Prevalence of and factors related to anxiety and depression symptoms among married patients with gynecological malignancies in China.

Asian journal of psychiatry
OBJECTIVE: This study aims to investigate the prevalence of anxiety and depression among married patients with gynecological malignancies in China and then explores factors related to anxiety and depression.

Automatic hyoid bone detection in fluoroscopic images using deep learning.

Scientific reports
The displacement of the hyoid bone is one of the key components evaluated in the swallow study, as its motion during swallowing is related to overall swallowing integrity. In daily research settings, experts visually detect the hyoid bone in the vide...

Diagnostic outcomes of esophageal cancer by artificial intelligence using convolutional neural networks.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: The prognosis of esophageal cancer is relatively poor. Patients are usually diagnosed at an advanced stage when it is often too late for effective treatment. Recently, artificial intelligence (AI) using deep learning has made rem...

Remotely Controlled Mandibular Positioning During Drug-Induced Sleep Endoscopy Toward Mandibular Advancement Device Therapy: Feasibility and Protocol.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
STUDY OBJECTIVES: The potential of a remotely controlled mandibular positioner (RCMP) during sleep studies in individual patients suffering from obstructive sleep apnea (OSA) for the determination of the effective target protrusive position (ETPP) of...