AIMC Topic: Aged, 80 and over

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A Comparative Study of the Diagnostic Potential of Plasma and Erythrocytic α-Synuclein in Parkinson's Disease.

Neuro-degenerative diseases
BACKGROUND: Parkinson's disease (PD) is a neurodegenerative disease characterized by intracellular α-synuclein (α-Syn) deposition. Alternation of the α-Syn expression level in plasma or erythrocytes may be used as a potential PD biomarker. However, n...

Using machine learning to predict early readmission following esophagectomy.

The Journal of thoracic and cardiovascular surgery
OBJECTIVE: To establish a machine learning (ML)-based prediction model for readmission within 30 days (early readmission or early readmission) of patients based on their profile at index hospitalization for esophagectomy.

Emerging Pharmacotherapy and Health Care Needs of Patients in the Age of Artificial Intelligence and Digitalization.

The Annals of pharmacotherapy
Advances in the application of artificial intelligence, digitization, technology, iCloud computing, and wearable devices in health care predict an exciting future for health care professionals and our patients. Projections suggest an older, generally...

Deep learning COVID-19 detection bias: accuracy through artificial intelligence.

International orthopaedics
BACKGROUND: Detection of COVID-19 cases' accuracy is posing a conundrum for scientists, physicians, and policy-makers. As of April 23, 2020, 2.7 million cases have been confirmed, over 190,000 people are dead, and about 750,000 people are reported re...

Differentiation of Benign from Malignant Pulmonary Nodules by Using a Convolutional Neural Network to Determine Volume Change at Chest CT.

Radiology
Background Deep learning may help to improve computer-aided detection of volume (CADv) measurement of pulmonary nodules at chest CT. Purpose To determine the efficacy of a deep learning method for improving CADv for measuring the solid and ground-gla...

Deep Learning Automated Detection of Reticular Pseudodrusen from Fundus Autofluorescence Images or Color Fundus Photographs in AREDS2.

Ophthalmology
PURPOSE: To develop deep learning models for detecting reticular pseudodrusen (RPD) using fundus autofluorescence (FAF) images or, alternatively, color fundus photographs (CFP) in the context of age-related macular degeneration (AMD).

Deep learning-guided joint attenuation and scatter correction in multitracer neuroimaging studies.

Human brain mapping
PET attenuation correction (AC) on systems lacking CT/transmission scanning, such as dedicated brain PET scanners and hybrid PET/MRI, is challenging. Direct AC in image-space, wherein PET images corrected for attenuation and scatter are synthesized f...