AIMC Topic: Risk

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Garbage in, garbage out: mitigating risks and maximizing benefits of AI in research.

Nature Nov 1, 2023
Artificial Intelligence Research Risk
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Health Care Privacy Risks of AI Chatbots.

JAMA Jul 25, 2023
Artificial Intelligence Risk Delivery of Health Care Health Communication Privacy
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Influence of the stress level on the execution of the Grooved Pegboard Test.

The Journal of sports medicine and physical fitness Aug 1, 2022
BACKGROUND: The Grooved Pegboard Test (GPT) is a widely adopted test to evaluate manual dexterity. A factor that could influence the cognitive process is physical and mental stress, which could be controlled by respiration. Stress can be monitored th...
Humans Hand Strength Risk
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Single-Examination Risk Prediction of Severe Retinopathy of Prematurity.

Pediatrics Dec 1, 2021
BACKGROUND AND OBJECTIVES: Retinopathy of prematurity (ROP) is a leading cause of childhood blindness. Screening and treatment reduces this risk, but requires multiple examinations of infants, most of whom will not develop severe disease. Previous wo...
Risk Retinopathy of Prematurity Fundus Oculi Sensitivity and Specificity Early Diagnosis Humans Predictive Value of Tests Severity of Illness Index Gestational Age Artificial Intelligence Area Under Curve Infant, Newborn Logistic Models Birth Weight
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Advancing care for acute gastrointestinal bleeding using artificial intelligence.

Journal of gastroenterology and hepatology Feb 1, 2021
The future of gastrointestinal bleeding will include the integration of machine learning algorithms to enhance clinician risk assessment and decision making. Machine learning algorithms have shown promise in outperforming existing clinical risk score...
Machine Learning Delivery of Health Care Electronic Health Records Humans Neural Networks, Computer Acute Disease Endoscopy, Gastrointestinal Gastrointestinal Hemorrhage Risk Assessment Decision Making Triage Risk Outpatients Hemostasis
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Deep Learning and Risk Score Classification of Mild Cognitive Impairment and Alzheimer's Disease.

Journal of Alzheimer's disease : JAD Jan 1, 2021
BACKGROUND: Many neurocognitive and neuropsychological tests are used to classify early mild cognitive impairment (EMCI), late mild cognitive impairment (LMCI), and Alzheimer's disease (AD) from cognitive normal (CN). This can make it challenging for...
Neuropsychological Tests Aged, 80 and over Male Deep Learning Humans Cognitive Dysfunction Female Alzheimer Disease Aged Risk
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Synthetic minority oversampling of vital statistics data with generative adversarial networks.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2020
OBJECTIVE: Minority oversampling is a standard approach used for adjusting the ratio between the classes on imbalanced data. However, established methods often provide modest improvements in classification performance when applied to data with extrem...
Risk Stillbirth Vital Statistics Humans Neural Networks, Computer ROC Curve Models, Statistical Area Under Curve
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Emerging from AI utopia.

Science (New York, N.Y.) Apr 3, 2020
Humans Artificial Intelligence Pandemics COVID-19 Human Rights Human Rights Abuses Coronavirus Infections Female Risk Pneumonia, Viral Male Quarantine
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Using applied machine learning to predict healthcare utilization based on socioeconomic determinants of care.

The American journal of managed care Jan 1, 2020
OBJECTIVES: To determine if it is possible to risk-stratify avoidable utilization without clinical data and with limited patient-level data.
Alabama Georgia Patient Acceptance of Health Care Ohio Emergency Service, Hospital Adult Social Determinants of Health Humans Male Risk Child Machine Learning Socioeconomic Factors Infant Middle Aged Female Decision Trees Adolescent Hospitalization Child, Preschool Aged Young Adult
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Deep Q-learning for Predicting Asthma Attack with Considering Personalized Environmental Triggers' Risk Scores.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
The purpose of our present study was to develop a forecasting method that would help asthmatic individuals to take evasive action when the probability of an attack was at THEIR PERSONAL THRESHOLD levels. The results are encouraging. Risk factor analy...
Decision Making Probability Risk Humans Asthma Deep Learning
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