AIMC Topic: Follow-Up Studies

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Using high-dimensional machine learning methods to estimate an anatomical risk factor for Alzheimer's disease across imaging databases.

NeuroImage Aug 18, 2018
INTRODUCTION: The main goal of this work is to investigate the feasibility of estimating an anatomical index that can be used as an Alzheimer's disease (AD) risk factor in the Women's Health Initiative Magnetic Resonance Imaging Study (WHIMS-MRI) usi...
Risk Assessment Cognitive Dysfunction Follow-Up Studies Magnetic Resonance Imaging Alzheimer Disease Neuroimaging White Matter Humans Machine Learning Databases, Factual Prognosis Female Aged
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Predicting Post Neoadjuvant Axillary Response Using a Novel Convolutional Neural Network Algorithm.

Annals of surgical oncology Jul 5, 2018
OBJECTIVES: In the postneoadjuvant chemotherapy (NAC) setting, conventional radiographic complete response (rCR) is a poor predictor of pathologic complete response (pCR) of the axilla. We developed a convolutional neural network (CNN) algorithm to b...
Prognosis Retrospective Studies Female Aged Aged, 80 and over Young Adult Humans Neural Networks, Computer Algorithms Receptor, ErbB-2 Carcinoma, Ductal, Breast Receptors, Estrogen Chemotherapy, Adjuvant Antineoplastic Combined Chemotherapy Protocols Carcinoma, Lobular Neoadjuvant Therapy Follow-Up Studies Magnetic Resonance Imaging Neoplasm Invasiveness Axilla Adult Survival Rate Breast Neoplasms Biomarkers, Tumor Middle Aged ROC Curve
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Using natural language processing for identification of herpes zoster ophthalmicus cases to support population-based study.

Clinical & experimental ophthalmology Jul 4, 2018
IMPORTANCE: Diagnosis codes are inadequate for accurately identifying herpes zoster (HZ) ophthalmicus (HZO). There is significant lack of population-based studies on HZO due to the high expense of manual review of medical records.
Follow-Up Studies Population Surveillance Natural Language Processing Herpesvirus 3, Human Eye Infections, Viral Herpes Zoster Ophthalmicus Young Adult Adult Male Middle Aged Adolescent ROC Curve Humans Algorithms Retrospective Studies Female Reproducibility of Results Aged Aged, 80 and over
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Detection of Longitudinal Visual Field Progression in Glaucoma Using Machine Learning.

American journal of ophthalmology Jun 18, 2018
PURPOSE: Global indices of standard automated perimerty are insensitive to localized losses, while point-wise indices are sensitive but highly variable. Region-wise indices sit in between. This study introduces a machine learning-based index for glau...
Intraocular Pressure Male Middle Aged Disease Progression Diagnosis, Computer-Assisted Follow-Up Studies Vision Disorders Visual Fields Visual Field Tests Glaucoma, Open-Angle Tonometry, Ocular Gonioscopy Humans Machine Learning Female Aged Cross-Sectional Studies
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Machine-learning-derived classifier predicts absence of persistent pain after breast cancer surgery with high accuracy.

Breast cancer research and treatment Jun 6, 2018
BACKGROUND: Prevention of persistent pain following breast cancer surgery, via early identification of patients at high risk, is a clinical need. Supervised machine-learning was used to identify parameters that predict persistence of significant pain...
Aged Adult Breast Neoplasms Middle Aged Time Factors Follow-Up Studies Humans Machine Learning Prognosis Female Reproducibility of Results Risk Factors Pain, Postoperative Mastectomy Supervised Machine Learning
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A comparison of statistical and machine-learning techniques in evaluating the association between dietary patterns and 10-year cardiometabolic risk (2002-2012): the ATTICA study.

The British journal of nutrition May 23, 2018
Statistical methods are usually applied in examining diet-disease associations, whereas factor analysis is commonly used for dietary pattern recognition. Recently, machine learning (ML) has been also proposed as an alternative technique in health cla...
Prospective Studies Female Reproducibility of Results Risk Factors Aged Aged, 80 and over Young Adult Adult Male Cardiovascular Diseases Middle Aged Diet Hypercholesterolemia Humans Models, Statistical Machine Learning Blood Pressure Data Interpretation, Statistical Risk Assessment Sex Factors Adolescent Linear Models Incidence Pattern Recognition, Automated Hypertension Diabetes Mellitus Follow-Up Studies
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Machine learning: a useful radiological adjunct in determination of a newly diagnosed glioma's grade and IDH status.

Journal of neuro-oncology May 16, 2018
INTRODUCTION: Machine learning methods have been introduced as a computer aided diagnostic tool, with applications to glioma characterisation on MRI. Such an algorithmic approach may provide a useful adjunct for a rapid and accurate diagnosis of a gl...
Isocitrate Dehydrogenase Image Processing, Computer-Assisted Humans Glioma Machine Learning Follow-Up Studies Algorithms Aged Magnetic Resonance Imaging Retrospective Studies Adult Neoplasm Grading Female Brain Neoplasms Mutation Male Middle Aged ROC Curve
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Evolution of upper limb kinematics four years after subacute robot-assisted rehabilitation in stroke patients.

The International journal of neuroscience Apr 25, 2018
To assess functional status and robot-based kinematic measures four years after subacute robot-assisted rehabilitation in hemiparesis. Twenty-two patients with stroke-induced hemiparesis underwent a ≥3-month upper limb combined program of robot-ass...
Stroke Paresis Upper Extremity Stroke Rehabilitation Cohort Studies Time Factors Follow-Up Studies Recovery of Function Robotics Occupational Therapy Female Aged Adult Humans Biomechanical Phenomena Retrospective Studies Male Middle Aged
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Assessing Breast Cancer Risk with an Artificial Neural Network.

Asian Pacific journal of cancer prevention : APJCP Apr 25, 2018
Objectives: Radiologists face uncertainty in making decisions based on their judgment of breast cancer risk. Artificial intelligence and machine learning techniques have been widely applied in detection/recognition of cancer. This study aimed to esta...
ROC Curve Follow-Up Studies Mammography Female Breast Humans Aged Neural Networks, Computer Breast Neoplasms Machine Learning Middle Aged Algorithms Case-Control Studies Prognosis Diagnosis, Computer-Assisted Retrospective Studies
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Machine Learning Methods Improve Prognostication, Identify Clinically Distinct Phenotypes, and Detect Heterogeneity in Response to Therapy in a Large Cohort of Heart Failure Patients.

Journal of the American Heart Association Apr 12, 2018
BACKGROUND: Whereas heart failure (HF) is a complex clinical syndrome, conventional approaches to its management have treated it as a singular disease, leading to inadequate patient care and inefficient clinical trials. We hypothesized that applying ...
Stroke Volume Middle Aged Humans Follow-Up Studies Algorithms Machine Learning Registries Phenotype Heart Failure Sweden Prognosis Aged Diuretics Retrospective Studies Angiotensin Receptor Antagonists Aged, 80 and over Female Angiotensin-Converting Enzyme Inhibitors Survival Rate Reproducibility of Results Cardiovascular Agents Male Adrenergic beta-Antagonists Ventricular Function, Left
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