AIMC Topic: Follow-Up Studies

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Cardiovascular/stroke risk prevention: A new machine learning framework integrating carotid ultrasound image-based phenotypes and its harmonics with conventional risk factors.

Indian heart journal Jun 18, 2020
MOTIVATION: Machine learning (ML)-based stroke risk stratification systems have typically focused on conventional risk factors (CRF) (AtheroRisk-conventional). Besides CRF, carotid ultrasound image phenotypes (CUSIP) have shown to be powerful phenoty...
Humans Machine Learning Ultrasonography Follow-Up Studies Stroke Phenotype Carotid Artery, Common Retrospective Studies Risk Factors Risk Assessment
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Diabetic Retinopathy Screening with Automated Retinal Image Analysis in a Primary Care Setting Improves Adherence to Ophthalmic Care.

Ophthalmology. Retina Jun 17, 2020
PURPOSE: Retinal screening examinations can prevent vision loss resulting from diabetes but are costly and highly underused. We hypothesized that artificial intelligence-assisted nonmydriatic point-of-care screening administered during primary care v...
Follow-Up Studies Retina Ambulatory Care Facilities Diabetic Retinopathy Artificial Intelligence Prospective Studies Female Male Middle Aged Primary Health Care Image Processing, Computer-Assisted Mass Screening Humans
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Improving blood glucose level predictability using machine learning.

Diabetes/metabolism research and reviews Jun 14, 2020
This study was designed to improve blood glucose level predictability and future hypoglycemic and hyperglycemic event alerts through a novel patient-specific supervised-machine-learning (SML) analysis of glucose level based on a continuous-glucose-mo...
Machine Learning Algorithms Biomarkers Prognosis Female Humans Diabetes Mellitus, Type 1 Young Adult Follow-Up Studies Adult Hypoglycemia Male Israel Adolescent Blood Glucose Self-Monitoring Blood Glucose
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Predicting individual improvement in schizophrenia symptom severity at 1-year follow-up: Comparison of connectomic, structural, and clinical predictors.

Human brain mapping May 29, 2020
In a machine learning setting, this study aims to compare the prognostic utility of connectomic, brain structural, and clinical/demographic predictors of individual change in symptom severity in individuals with schizophrenia. Symptom severity at bas...
Schizophrenia Antipsychotic Agents Neuroimaging Gray Matter Humans Prognosis Male Machine Learning Connectome Cerebral Cortex Female Severity of Illness Index Default Mode Network Young Adult Follow-Up Studies Adult Magnetic Resonance Imaging Sensitivity and Specificity
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A machine learning model that classifies breast cancer pathologic complete response on MRI post-neoadjuvant chemotherapy.

Breast cancer research : BCR May 28, 2020
BACKGROUND: For breast cancer patients undergoing neoadjuvant chemotherapy (NAC), pathologic complete response (pCR; no invasive or in situ) cannot be assessed non-invasively so all patients undergo surgery. The aim of our study was to develop and va...
Magnetic Resonance Imaging Carcinoma, Ductal, Breast Carcinoma, Lobular ROC Curve Antineoplastic Combined Chemotherapy Protocols Prognosis Neoadjuvant Therapy Humans Retrospective Studies Follow-Up Studies Machine Learning Female Breast Neoplasms Middle Aged
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Artificial Intelligence-Assisted System in Postoperative Follow-up of Orthopedic Patients: Exploratory Quantitative and Qualitative Study.

Journal of medical Internet research May 26, 2020
BACKGROUND: Patient follow-up is an essential part of hospital ward management. With the development of deep learning algorithms, individual follow-up assignments might be completed by artificial intelligence (AI). We developed an AI-assisted follow-...
Postoperative Period Humans Orthopedics Artificial Intelligence Qualitative Research Follow-Up Studies Evaluation Studies as Topic
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Predicting Survival After Extracorporeal Membrane Oxygenation by Using Machine Learning.

The Annals of thoracic surgery May 23, 2020
BACKGROUND: Venoarterial (VA) extracorporeal membrane oxygenation (ECMO) undoubtedly saves many lives, but it is associated with a high degree of patient morbidity, mortality, and resource use. This study aimed to develop a machine learning algorithm...
Prognosis Retrospective Studies Female Aged Survival Rate Male Middle Aged Hospital Mortality ROC Curve Humans Machine Learning Follow-Up Studies Extracorporeal Membrane Oxygenation New York Shock, Cardiogenic
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Machine-learning based exploration of determinants of gray matter volume in the KORA-MRI study.

Scientific reports May 20, 2020
To identify the most important factors that impact brain volume, while accounting for potential collinearity, we used a data-driven machine-learning approach. Gray Matter Volume (GMV) was derived from magnetic resonance imaging (3T, FLAIR) and adjust...
Gray Matter Prediabetic State Life Style Confounding Factors, Epidemiologic Magnetic Resonance Imaging Models, Neurological Organ Size Linear Models Germany Case-Control Studies Diabetes Mellitus, Type 2 Glomerular Filtration Rate Follow-Up Studies Humans Machine Learning Prospective Studies Female Cross-Sectional Studies Male Cardiovascular Diseases Middle Aged
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Stability Assessment of Intracranial Aneurysms Using Machine Learning Based on Clinical and Morphological Features.

Translational stroke research May 19, 2020
Machine learning (ML) as a novel approach could help clinicians address the challenge of accurate stability assessment of unruptured intracranial aneurysms (IAs). We developed multiple ML models for IA stability assessment and compare their performan...
Follow-Up Studies Aged Humans Intracranial Aneurysm Adult Machine Learning Male Retrospective Studies Middle Aged Female ROC Curve
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Applying machine learning methods to develop a successful aging maintenance prediction model based on physical fitness tests.

Geriatrics & gerontology international May 1, 2020
AIM: The purpose of this study was to develop a machine learning prediction model for successful aging (SA) based on physical fitness tests.
Exercise China Surveys and Questionnaires ROC Curve Logistic Models Sensitivity and Specificity Male Aging Middle Aged Physical Fitness Independent Living Healthy Aging Follow-Up Studies Decision Trees Predictive Value of Tests Geriatric Assessment Humans Machine Learning Female Aged Aged, 80 and over
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