AIMC Topic: Risk Assessment

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Deep Learning for Fall Risk Assessment With Inertial Sensors: Utilizing Domain Knowledge in Spatio-Temporal Gait Parameters.

IEEE journal of biomedical and health informatics Dec 11, 2019
Fall risk assessment is essential to predict and prevent falls in geriatric populations, especially patients with life-long conditions like neurological disorders. Inertial sensor-based pervasive gait analysis systems have become viable means to faci...
Equipment Design Gait Analysis Risk Assessment Deep Learning Accidental Falls Wearable Electronic Devices Humans Algorithms Female Aged Aged, 80 and over Male
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Using machine learning models to improve stroke risk level classification methods of China national stroke screening.

BMC medical informatics and decision making Dec 10, 2019
BACKGROUND: With the character of high incidence, high prevalence and high mortality, stroke has brought a heavy burden to families and society in China. In 2009, the Ministry of Health of China launched the China national stroke screening and interv...
Humans Neural Networks, Computer Risk Assessment China Incidence Logistic Models Mass Screening Machine Learning Algorithms Decision Support Techniques Adult Decision Trees Stroke
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Representation learning in intraoperative vital signs for heart failure risk prediction.

BMC medical informatics and decision making Dec 9, 2019
BACKGROUND: The probability of heart failure during the perioperative period is 2% on average and it is as high as 17% when accompanied by cardiovascular diseases in China. It has been the most significant cause of postoperative death of patients. Ho...
Monitoring, Intraoperative Decision Trees Area Under Curve Heart Failure Intraoperative Complications Humans Machine Learning Neural Networks, Computer Risk Sensitivity and Specificity Risk Assessment China Vital Signs
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Developing algorithms to predict adult onset internalizing disorders: An ensemble learning approach.

Journal of psychiatric research Dec 6, 2019
A growing literature is utilizing machine learning methods to develop psychopathology risk algorithms that can be used to inform preventive intervention. However, efforts to develop algorithms for internalizing disorder onset have been limited. The g...
Depressive Disorder Panic Disorder Bipolar Disorder Humans Health Surveys Longitudinal Studies Phobia, Social Machine Learning Adult Risk Assessment Anxiety Disorders
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Development and validation of a risk prediction model to diagnose Barrett's oesophagus (MARK-BE): a case-control machine learning approach.

The Lancet. Digital health Dec 5, 2019
BACKGROUND: Screening for Barrett's Oesophagus (BE) relies on endoscopy which is invasive and has a low yield. This study aimed to develop and externally validate a simple symptom and risk-factor questionnaire to screen for patients with BE.
Risk Assessment Female Case-Control Studies Aged Humans United Kingdom Male Barrett Esophagus Machine Learning Middle Aged Forecasting Prospective Studies
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Reconstruction error based deep neural networks for coronary heart disease risk prediction.

PloS one Dec 5, 2019
Coronary heart disease (CHD) is one of the leading causes of death worldwide; if suffering from CHD and being in its end-stage, the most advanced treatments are required, such as heart surgery and heart transplant. Moreover, it is not easy to diagnos...
Risk Factors Risk Assessment Deep Learning Humans Coronary Disease Neural Networks, Computer Algorithms Reproducibility of Results
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Identifying undetected dementia in UK primary care patients: a retrospective case-control study comparing machine-learning and standard epidemiological approaches.

BMC medical informatics and decision making Dec 2, 2019
BACKGROUND: Identifying dementia early in time, using real world data, is a public health challenge. As only two-thirds of people with dementia now ultimately receive a formal diagnosis in United Kingdom health systems and many receive it late in the...
Female Aged Male Risk Assessment Machine Learning Algorithms Retrospective Studies Electronic Health Records Logistic Models Support Vector Machine Bayes Theorem United Kingdom State Medicine Case-Control Studies Dementia Humans Primary Health Care Neural Networks, Computer Computational Biology
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Machine learning with sparse nutrition data to improve cardiovascular mortality risk prediction in the USA using nationally randomly sampled data.

BMJ open Nov 28, 2019
OBJECTIVES: We aimed to test whether or not adding (1) nutrition predictor variables and/or (2) using machine learning models improves cardiovascular death prediction versus standard Cox models without nutrition predictor variables.
Diet Records Middle Aged Female Nutrition Surveys Risk Assessment Humans United States Aged Machine Learning Proportional Hazards Models Male Algorithms Cardiovascular Diseases Retrospective Studies
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Deep learning modeling using normal mammograms for predicting breast cancer risk.

Medical physics Nov 19, 2019
PURPOSE: To investigate two deep learning-based modeling schemes for predicting short-term risk of developing breast cancer using prior normal screening digital mammograms in a case-control setting.
Breast Neoplasms Middle Aged Risk Assessment Case-Control Studies Models, Theoretical Deep Learning Humans Female Mammography Cohort Studies Retrospective Studies Aged Aged, 80 and over Adult
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Machine Learning-Based Prediction Models for 30-Day Readmission after Hospitalization for Chronic Obstructive Pulmonary Disease.

COPD Nov 11, 2019
While machine learning approaches can enhance prediction ability, little is known about their ability to predict 30-day readmission after hospitalization for Chronic Obstructive Pulmonary Disease (COPD). We identified patients aged ≥40 years with unp...
Aged, 80 and over Adult Pulmonary Disease, Chronic Obstructive Male Middle Aged Risk Assessment Logistic Models Japan Patient Readmission Prognosis Humans Clinical Decision Rules Female Machine Learning Hospitalization Databases, Factual Aged
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