AIMC Topic: Time Factors

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A novel model for predicting the outcome of intracerebral hemorrhage: Based on 1186 Patients.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Jun 8, 2020
OBJECTIVE: To establish a model for predicting the outcome according to the clinical and computed tomography(CT) image data of patients with intracerebral hemorrhage(ICH).
Predictive Value of Tests Risk Factors Male Middle Aged Risk Assessment Nomograms Support Vector Machine Cerebral Hemorrhage China Time Factors Prognosis Retrospective Studies Tomography, X-Ray Computed Female Humans Decision Support Techniques
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Effects of gait exercise assist robot (GEAR) on subjects with chronic stroke: A randomized controlled pilot trial.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Jun 5, 2020
OBJECTIVE: The aim of this study was to investigate whether gait training using the Gait Exercise Assist Robot (GEAR) is more effective for improving gait ability than treadmill gait training in chronic stroke subjects.
Male Gait Middle Aged Japan Pilot Projects Time Factors Exercise Therapy Treatment Outcome Humans Gait Analysis Recovery of Function Female Stroke Rehabilitation Chronic Disease Aged Robotics Stroke
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Using machine learning models to predict the initiation of renal replacement therapy among chronic kidney disease patients.

PloS one Jun 5, 2020
Starting renal replacement therapy (RRT) for patients with chronic kidney disease (CKD) at an optimal time, either with hemodialysis or kidney transplantation, is crucial for patient's well-being and for successful management of the condition. In thi...
Time Factors ROC Curve Clinical Decision-Making Humans Renal Insufficiency, Chronic Models, Biological Time-to-Treatment Taiwan Machine Learning Disease Progression Datasets as Topic Retrospective Studies Comorbidity Severity of Illness Index Renal Replacement Therapy
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Fully automated intracranial aneurysm detection and segmentation from digital subtraction angiography series using an end-to-end spatiotemporal deep neural network.

Journal of neurointerventional surgery May 29, 2020
BACKGROUND: Intracranial aneurysms (IAs) are common in the population and may cause death.
Deep Learning Time Factors Contrast Media Angiography, Digital Subtraction Cerebral Angiography Intracranial Aneurysm Aged Adult Male Middle Aged Humans Neural Networks, Computer Retrospective Studies Female
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Automated computer-assisted detection system for cerebral aneurysms in time-of-flight magnetic resonance angiography using fully convolutional network.

Biomedical engineering online May 29, 2020
BACKGROUND: As the rupture of cerebral aneurysm may lead to fatal results, early detection of unruptured aneurysms may save lives. At present, the contrast-unenhanced time-of-flight magnetic resonance angiography is one of the most commonly used meth...
Middle Aged Diagnosis, Computer-Assisted Adolescent Time Factors Aged Young Adult Adult Male Image Processing, Computer-Assisted Automation Magnetic Resonance Angiography Intracranial Aneurysm Humans Neural Networks, Computer Female
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Developing knowledge-based planning for gynaecological and rectal cancers: a clinical validation of RapidPlan.

Journal of medical radiation sciences May 25, 2020
INTRODUCTION: To create and clinically validate knowledge-based planning (KBP) models for gynaecologic (GYN) and rectal cancer patients. Assessment of ecologic generalisability and predictive validity of conventional planning versus single calculatio...
Reproducibility of Results Humans Rectal Neoplasms Genital Neoplasms, Female Time Factors Female Knowledge Bases Radiotherapy, Intensity-Modulated Radiotherapy Planning, Computer-Assisted Dose Fractionation, Radiation
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A Machine Learning-Based Approach for Predicting Patient Punctuality in Ambulatory Care Centers.

International journal of environmental research and public health May 24, 2020
Late-arriving patients have become a prominent concern in several ambulatory care clinics across the globe. Accommodating them could lead to detrimental ramifications such as schedule disruption and increased waiting time for forthcoming patients, wh...
Time Factors Logistic Models United States Medicare Machine Learning Female Aged Humans Appointments and Schedules Male Neural Networks, Computer Ambulatory Care
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Developing an Improved Statistical Approach for Survival Estimation in Bone Metastases Management: The Bone Metastases Ensemble Trees for Survival (BMETS) Model.

International journal of radiation oncology, biology, physics May 22, 2020
PURPOSE: To determine whether a machine learning approach optimizes survival estimation for patients with symptomatic bone metastases (SBM), we developed the Bone Metastases Ensemble Trees for Survival (BMETS) to predict survival using 27 prognostic ...
Reproducibility of Results Male Middle Aged Steroids Bone Neoplasms Area Under Curve Analgesics, Opioid Time Factors Kaplan-Meier Estimate Pelvic Bones Machine Learning Life Expectancy Palliative Care Algorithms Blood Cell Count Karnofsky Performance Status Humans Prognosis Spinal Neoplasms Female Proportional Hazards Models
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Spatio-temporal deep learning methods for motion estimation using 4D OCT image data.

International journal of computer assisted radiology and surgery May 22, 2020
PURPOSE: Localizing structures and estimating the motion of a specific target region are common problems for navigation during surgical interventions. Optical coherence tomography (OCT) is an imaging modality with a high spatial and temporal resoluti...
Deep Learning Time Factors Imaging, Three-Dimensional Humans Image Processing, Computer-Assisted Tomography, Optical Coherence Robotic Surgical Procedures Algorithms Equipment Design Motion Tissue Distribution
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Retip: Retention Time Prediction for Compound Annotation in Untargeted Metabolomics.

Analytical chemistry May 21, 2020
Unidentified peaks remain a major problem in untargeted metabolomics by LC-MS/MS. Confidence in peak annotations increases by combining MS/MS matching and retention time. We here show how retention times can be predicted from molecular structures. Tw...
Humans Machine Learning Time Factors Organic Chemicals Metabolomics Chromatography, Liquid Tandem Mass Spectrometry
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