AIMC Topic: Aged, 80 and over

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MRI-based attenuation correction for brain PET/MRI based on anatomic signature and machine learning.

Physics in medicine and biology Jan 7, 2019
Deriving accurate attenuation maps for PET/MRI remains a challenging problem because MRI voxel intensities are not related to properties of photon attenuation and bone/air interfaces have similarly low signal. This work presents a learning-based meth...
Machine Learning Retrospective Studies Tomography, X-Ray Computed Female Reproducibility of Results Humans Male Middle Aged Image Processing, Computer-Assisted Magnetic Resonance Imaging Multimodal Imaging Positron-Emission Tomography Aged Aged, 80 and over Young Adult Adult Brain Neoplasms
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Screening for cardiac contractile dysfunction using an artificial intelligence-enabled electrocardiogram.

Nature medicine Jan 7, 2019
Asymptomatic left ventricular dysfunction (ALVD) is present in 3-6% of the general population, is associated with reduced quality of life and longevity, and is treatable when found. An inexpensive, noninvasive screening tool for ALVD in the doctor's ...
Neural Networks, Computer Artificial Intelligence Female Aged Aged, 80 and over Adult Humans Electrocardiography Mass Screening Heart Myocardial Contraction Sensitivity and Specificity Male Stroke Volume Middle Aged ROC Curve
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Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer.

La Radiologia medica Jan 3, 2019
OBJECTIVE: To develop different radiomic models based on the magnetic resonance imaging (MRI) radiomic features and machine learning methods to predict early intensity-modulated radiation therapy (IMRT) response, Gleason scores (GS) and prostate canc...
Machine Learning Neoplasm Staging Humans Middle Aged Treatment Outcome Magnetic Resonance Imaging Predictive Value of Tests Prostatic Neoplasms Neoplasm Grading Image Interpretation, Computer-Assisted Radiotherapy, Intensity-Modulated Prospective Studies Aged Aged, 80 and over Male
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Predictors of Nodal and Metastatic Failure in Early Stage Non-small-cell Lung Cancer After Stereotactic Body Radiation Therapy.

Clinical lung cancer Dec 29, 2018
INTRODUCTION/BACKGROUND: Many patients with early stage non-small-cell lung cancer (ES-NSCLC) undergoing stereotactic body radiation therapy (SBRT) develop metastases, which is associated with poor outcomes. We sought to identify factors predictive o...
Humans Lung Neoplasms Carcinoma, Non-Small-Cell Lung Follow-Up Studies Lymphatic Metastasis Neoplasm Staging Treatment Failure Aged, 80 and over Tumor Burden Adult Radiotherapy Dosage Prognosis Male Radiosurgery Retrospective Studies Middle Aged Female Disease Progression Risk Factors Aged
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Efficacy and safety of CT-guided high-dose-rate interstitial brachytherapy in primary and secondary malignancies of the pancreas.

European journal of radiology Dec 28, 2018
PURPOSE: To evaluate efficacy and safety of CT-guided iBT in patients with primary and secondary malignancies of the pancreas.
Neoplasm Recurrence, Local Brachytherapy Neoplasms, Second Primary Radiography, Interventional Aged, 80 and over Radiotherapy Dosage Adult Male Middle Aged Treatment Outcome Humans Pancreatic Neoplasms Retrospective Studies Tomography, X-Ray Computed Female Aged
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A novel prediction method for lymph node involvement in endometrial cancer: machine learning.

International journal of gynecological cancer : official journal of the International Gynecological Cancer Society Dec 28, 2018
OBJECTIVE: The necessity of lymphadenectomy and the prediction of lymph node involvement (LNI) in endometrial cancer (EC) have been hotly-debated questions in recent years. Machine learning is a broad field that can produce results and estimations. I...
Aged, 80 and over Adult Middle Aged Lymph Nodes Follow-Up Studies Lymph Node Excision Models, Statistical Predictive Value of Tests Endometrial Neoplasms Humans Machine Learning Retrospective Studies Female Aged
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Local Infiltration Analgesia With Liposomal Bupivacaine Improves Early Outcomes After Total Knee Arthroplasty: 24-Hour Data From the PILLAR Study.

The Journal of arthroplasty Dec 25, 2018
BACKGROUND: Enhanced postoperative care pathways have shifted total knee arthroplasty (TKA) to outpatient and short-stay settings, placing greater emphasis on predischarge outcomes. In this study, we report prespecified secondary and tertiary end poi...
Analgesics, Opioid Middle Aged Arthroplasty, Replacement, Knee Anesthetics, Local Humans Double-Blind Method Pain Management Analgesia Pain, Postoperative Female Bupivacaine Aged Aged, 80 and over Male
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Predicting persistent depressive symptoms in older adults: A machine learning approach to personalised mental healthcare.

Journal of affective disorders Dec 25, 2018
BACKGROUND: Depression causes significant physical and psychosocial morbidity. Predicting persistence of depressive symptoms could permit targeted prevention, and lessen the burden of depression. Machine learning is a rapidly expanding field, and suc...
Depression Logistic Models Follow-Up Studies Humans Age Factors Machine Learning Predictive Value of Tests Algorithms Aged Decision Support Techniques Aged, 80 and over Delivery of Health Care Male Female Risk Assessment Psychiatric Status Rating Scales
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Hierarchical Fully Convolutional Network for Joint Atrophy Localization and Alzheimer's Disease Diagnosis Using Structural MRI.

IEEE transactions on pattern analysis and machine intelligence Dec 21, 2018
Structural magnetic resonance imaging (sMRI) has been widely used for computer-aided diagnosis of neurodegenerative disorders, e.g., Alzheimer's disease (AD), due to its sensitivity to morphological changes caused by brain atrophy. Recently, a few de...
Magnetic Resonance Imaging Supervised Machine Learning Alzheimer Disease Image Interpretation, Computer-Assisted Atrophy Brain Female Aged Aged, 80 and over Humans Male Neural Networks, Computer
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From Machine to Machine: An OCT-Trained Deep Learning Algorithm for Objective Quantification of Glaucomatous Damage in Fundus Photographs.

Ophthalmology Dec 20, 2018
PURPOSE: Previous approaches using deep learning (DL) algorithms to classify glaucomatous damage on fundus photographs have been limited by the requirement for human labeling of a reference training set. We propose a new approach using quantitative s...
Optic Disk Retinal Ganglion Cells Visual Fields Visual Field Tests Optic Nerve Diseases ROC Curve Visual Acuity Tomography, Optical Coherence Fundus Oculi Nerve Fibers Photography Glaucoma, Open-Angle Tonometry, Ocular Gonioscopy Humans Algorithms Female Aged Aged, 80 and over Cross-Sectional Studies Intraocular Pressure Male Middle Aged Deep Learning
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