AIMC Topic: Aged, 80 and over

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Predicting the risk of asthma attacks in children, adolescents and adults: protocol for a machine learning algorithm derived from a primary care-based retrospective cohort.

BMJ open Jul 23, 2020
INTRODUCTION: Most asthma attacks and subsequent deaths are potentially preventable. We aim to develop a prognostic tool for identifying patients at high risk of asthma attacks in primary care by leveraging advances in machine learning.
Humans Adult Primary Health Care Machine Learning Asthma Algorithms Middle Aged Retrospective Studies Adolescent Risk Factors Child Aged Aged, 80 and over Young Adult
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: deep learning-based radiomics for the time-to-event outcome prediction in lung cancer.

Scientific reports Jul 23, 2020
Hand-crafted radiomics has been used for developing models in order to predict time-to-event clinical outcomes in patients with lung cancer. Hand-crafted features, however, are pre-defined and extracted without taking the desired target into account....
Humans Deep Learning Aged Databases, Factual Lung Neoplasms Aged, 80 and over Tomography, X-Ray Computed Predictive Value of Tests Survival Rate Female Disease-Free Survival Male Positron-Emission Tomography Middle Aged
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Radiogenomics for predicting p53 status, PD-L1 expression, and prognosis with machine learning in pancreatic cancer.

British journal of cancer Jul 21, 2020
BACKGROUND: Radiogenomics is an emerging field that integrates "Radiomics" and "Genomics". In the current study, we aimed to predict the genetic information of pancreatic tumours in a simple, inexpensive, and non-invasive manner, using cancer imaging...
Humans Machine Learning Prognosis Retrospective Studies Tomography, X-Ray Computed Female Imaging Genomics Pancreatic Neoplasms Aged Mutation Aged, 80 and over Carcinoma, Pancreatic Ductal Male Tumor Suppressor Protein p53 Middle Aged Immunohistochemistry B7-H1 Antigen
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Cortical surface registration using unsupervised learning.

NeuroImage Jul 20, 2020
Non-rigid cortical registration is an important and challenging task due to the geometric complexity of the human cortex and the high degree of inter-subject variability. A conventional solution is to use a spherical representation of surface propert...
Magnetic Resonance Imaging Unsupervised Machine Learning Alzheimer Disease Neuroimaging Cerebral Cortex Male Aging Deep Learning Cognitive Dysfunction Models, Theoretical Female Humans Aged Aged, 80 and over Young Adult Adult
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Machine-learning approach to predict on-road driving ability in healthy older people.

Psychiatry and clinical neurosciences Jul 20, 2020
AIM: In Japan, fatal traffic accidents due to older drivers are on the rise. Considering that approximately half the older drivers who have caused fatal accidents are cognitively normal healthy people, it has been required to detect older drivers who...
Humans Support Vector Machine Accidents, Traffic Japan Automobile Driving Psychomotor Performance Neuropsychological Tests Female Aged Aged, 80 and over Male Aging
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Incremental Image Noise Reduction in Coronary CT Angiography Using a Deep Learning-Based Technique with Iterative Reconstruction.

Korean journal of radiology Jul 17, 2020
OBJECTIVE: To assess the feasibility of applying a deep learning-based denoising technique to coronary CT angiography (CCTA) along with iterative reconstruction for additional noise reduction.
Coronary Artery Disease Signal-To-Noise Ratio Computed Tomography Angiography Adult Male Humans Middle Aged Retrospective Studies Deep Learning Female Radiographic Image Interpretation, Computer-Assisted Aged Aged, 80 and over
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Comparison of machine learning algorithms to predict clinically significant prostate cancer of the peripheral zone with multiparametric MRI using clinical assessment categories and radiomic features.

European radiology Jul 16, 2020
OBJECTIVES: To analyze the performance of radiological assessment categories and quantitative computational analysis of apparent diffusion coefficient (ADC) maps using variant machine learning algorithms to differentiate clinically significant versus...
Machine Learning Biopsy Algorithms Prostatectomy Retrospective Studies Diffusion Magnetic Resonance Imaging Reproducibility of Results Multiparametric Magnetic Resonance Imaging Aged Humans Cluster Analysis Aged, 80 and over Principal Component Analysis Adult Area Under Curve Male Prostatic Neoplasms Middle Aged Prostate Treatment Outcome Support Vector Machine
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Fully automated quantification of left ventricular volumes and function in cardiac MRI: clinical evaluation of a deep learning-based algorithm.

The international journal of cardiovascular imaging Jul 16, 2020
To investigate the performance of a deep learning-based algorithm for fully automated quantification of left ventricular (LV) volumes and function in cardiac MRI. We retrospectively analysed MR examinations of 50 patients (74% men, median age 57 year...
Humans Young Adult Adult Male Ventricular Function, Left Middle Aged Diagnosis, Computer-Assisted Retrospective Studies Female Reproducibility of Results Aged Aged, 80 and over Heart Diseases Image Interpretation, Computer-Assisted Automation Magnetic Resonance Imaging, Cine Deep Learning Adolescent Predictive Value of Tests Feasibility Studies Heart Ventricles
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Outcome prediction with resting-state functional connectivity after cardiac arrest.

Scientific reports Jul 16, 2020
Predicting outcome in comatose patients after successful cardiopulmonary resuscitation is challenging. Our primary aim was to assess the potential contribution of resting-state-functional magnetic resonance imaging (RS-fMRI) in predicting neurologica...
Thalamus Cardiopulmonary Resuscitation Heart Arrest Coma Magnetic Resonance Imaging Brain Mapping Consciousness Neural Pathways Nerve Net Prospective Studies Prognosis Clinical Decision-Making Female Aged Aged, 80 and over Young Adult Adult Male Middle Aged Adolescent Humans Machine Learning
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Predicting respiratory failure after pulmonary lobectomy using machine learning techniques.

Surgery Jul 15, 2020
BACKGROUND: When pulmonary complications occur, postlobectomy patients have a higher mortality rate, increased length of stay, and higher readmission rates. Because of a lack of high-quality consolidated clinical data, it is challenging to assess and...
Adolescent Pneumonectomy Respiratory Insufficiency Male Middle Aged Risk Assessment Postoperative Complications Lung Humans Machine Learning Clinical Decision-Making Female Risk Factors Aged Aged, 80 and over Young Adult Adult Sensitivity and Specificity
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