AIMC Topic: Clinical Decision Rules

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A Continuously Benchmarked and Crowdsourced Challenge for Rapid Development and Evaluation of Models to Predict COVID-19 Diagnosis and Hospitalization.

JAMA network open Oct 1, 2021
IMPORTANCE: Machine learning could be used to predict the likelihood of diagnosis and severity of illness. Lack of COVID-19 patient data has hindered the data science community in developing models to aid in the response to the pandemic.
Male Middle Aged Infant Severity of Illness Index Adolescent Hospitalization Aged Aged, 80 and over Young Adult Adult Benchmarking COVID-19 Testing Crowdsourcing Washington Clinical Decision Rules Humans Child, Preschool COVID-19 Child Machine Learning Algorithms ROC Curve Prognosis Models, Statistical Female Area Under Curve Infant, Newborn
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Prediction Model Using Machine Learning for Mortality in Patients with Heart Failure.

The American journal of cardiology Jul 7, 2021
Heart Failure (HF) is a major cause of morbidity and mortality in the US. With aging of the US population, the public health burden of HF is enormous. We aimed to develop an ensemble prediction model for 30-day mortality after discharge using machine...
Heart Failure Mortality Clinical Decision Rules Aged Humans Aged, 80 and over Machine Learning Male Female Middle Aged Hospitalization Cause of Death
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Automatic Detection of Thyroid and Adrenal Incidentals Using Radiology Reports and Deep Learning.

The Journal of surgical research May 18, 2021
BACKGROUND: Computed tomography (CT) is commonly performed when evaluating trauma patients with up to 55% showing incidental findings. Current workflows to identify and inform patients are time-consuming and prone to error. Our objective was to autom...
Humans Algorithms Retrospective Studies Tomography, X-Ray Computed Female Deep Learning Thyroid Neoplasms Adrenal Gland Neoplasms Wounds and Injuries Incidental Findings Aged Adult Sensitivity and Specificity Male Middle Aged Clinical Decision Rules
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Machine Learning Algorithms for Predicting Fatty Liver Disease.

Annals of nutrition & metabolism Apr 13, 2021
BACKGROUND: Fatty liver disease (FLD) has become a rampant condition. It is associated with a high rate of morbidity and mortality in a population. The condition is commonly referred as FLD. Early prediction of FLD would allow patients to take necess...
Predictive Value of Tests Area Under Curve Humans Male Machine Learning Middle Aged Clinical Decision Rules Algorithms Risk Assessment Female Fatty Liver Adult Logistic Models
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Machine Learning Approaches to Determine Feature Importance for Predicting Infant Autopsy Outcome.

Pediatric and developmental pathology : the official journal of the Society for Pediatric Pathology and the Paediatric Pathology Society Mar 30, 2021
INTRODUCTION: Sudden unexpected death in infancy (SUDI) represents the commonest presentation of postneonatal death. We explored whether machine learning could be used to derive data driven insights for prediction of infant autopsy outcome.
Autopsy Sudden Infant Death Clinical Decision Rules Humans Infant, Newborn Machine Learning Infant Models, Statistical Decision Trees Feasibility Studies
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Deep learning diagnostic and risk-stratification pattern detection for COVID-19 in digital lung auscultations: clinical protocol for a case-control and prospective cohort study.

BMC pulmonary medicine Mar 24, 2021
BACKGROUND: Lung auscultation is fundamental to the clinical diagnosis of respiratory disease. However, auscultation is a subjective practice and interpretations vary widely between users. The digitization of auscultation acquisition and interpretati...
Triage COVID-19 Testing Auscultation Clinical Protocols Clinical Decision Rules Aged Aged, 80 and over Young Adult Adult Male Middle Aged Risk Assessment Case-Control Studies Deep Learning Adolescent COVID-19 Algorithms Prospective Studies Prognosis Female Humans
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A Machine Learning Prediction Model of Respiratory Failure Within 48 Hours of Patient Admission for COVID-19: Model Development and Validation.

Journal of medical Internet research Feb 10, 2021
BACKGROUND: Predicting early respiratory failure due to COVID-19 can help triage patients to higher levels of care, allocate scarce resources, and reduce morbidity and mortality by appropriately monitoring and treating the patients at greatest risk f...
Intubation, Intratracheal Early Warning Score Clinical Decision Rules Humans Machine Learning Retrospective Studies Logistic Models COVID-19 Female Male SARS-CoV-2 Middle Aged Triage Hospitalization Respiration, Artificial Emergency Service, Hospital Aged Hospitals Respiratory Insufficiency ROC Curve Patient Admission
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Artificial intelligence in sepsis early prediction and diagnosis using unstructured data in healthcare.

Nature communications Jan 29, 2021
Sepsis is a leading cause of death in hospitals. Early prediction and diagnosis of sepsis, which is critical in reducing mortality, is challenging as many of its signs and symptoms are similar to other less critical conditions. We develop an artifici...
Intensive Care Units Electronic Health Records Risk Assessment Prevalence Severity of Illness Index Humans Machine Learning Data Mining Early Diagnosis Sepsis Clinical Decision Rules Time Factors ROC Curve Predictive Value of Tests Feasibility Studies
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Early identification of patients with acute gastrointestinal bleeding using natural language processing and decision rules.

Journal of gastroenterology and hepatology Jan 25, 2021
BACKGROUND AND AIM: Guidelines recommend risk stratification scores in patients presenting with gastrointestinal bleeding (GIB), but such scores are uncommonly employed in practice. Automation and deployment of risk stratification scores in real time...
Humans Gastrointestinal Hemorrhage Algorithms Clinical Decision Rules Triage Natural Language Processing Electronic Health Records Emergency Service, Hospital Female Acute Disease Male Early Diagnosis Middle Aged Risk Assessment
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EffiCare: Better Prognostic Models via Resource-Efficient Health Embeddings.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
Recent medical prognostic models adapted from high data-resource fields like language processing have quickly grown in complexity and size. However, since medical data typically constitute low data-resource settings, performances on tasks like clinic...
Humans Electronic Health Records Machine Learning Benchmarking Prognosis Data Mining Intensive Care Units Information Storage and Retrieval Clinical Decision Rules
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