AIMC Topic: Disease Management

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Use of artificial intelligence in diagnosis of head and neck precancerous and cancerous lesions: A systematic review.

Oral oncology Jul 13, 2020
This systematic review analyses and describes the application and diagnostic accuracy of Artificial Intelligence (AI) methods used for detection and grading of potentially malignant (pre-cancerous) and cancerous head and neck lesions using whole slid...
Humans Disease Management Precancerous Conditions Disease Susceptibility Artificial Intelligence Head and Neck Neoplasms Algorithms Databases, Genetic Deep Learning Neoplasm Staging Neoplasm Grading
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Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors.

Sensors (Basel, Switzerland) Jul 10, 2020
Wearable continuous glucose monitoring (CGM) sensors are revolutionizing the treatment of type 1 diabetes (T1D). These sensors provide in real-time, every 1-5 min, the current blood glucose concentration and its rate-of-change, two key pieces of info...
Blood Glucose Self-Monitoring Humans Disease Management Artificial Intelligence Insulin Infusion Systems Wearable Electronic Devices Blood Glucose Diabetes Mellitus, Type 1
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Artificial intelligence in diagnosis and management of COVID-19 in dermatology.

Dermatologic therapy Jul 3, 2020
Humans Artificial Intelligence Pandemics COVID-19 Dermatology Disease Management Betacoronavirus Pneumonia, Viral SARS-CoV-2 Comorbidity Skin Diseases Coronavirus Infections
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An artificial intelligence decision support system for the management of type 1 diabetes.

Nature metabolism Jun 1, 2020
Type 1 diabetes (T1D) is characterized by pancreatic beta cell dysfunction and insulin depletion. Over 40% of people with T1D manage their glucose through multiple injections of long-acting basal and short-acting bolus insulin, so-called multiple dai...
Adult Blood Glucose Insulin Decision Support Systems, Clinical Algorithms Computer Simulation Reproducibility of Results Disease Management Glycemic Control Insulin Infusion Systems Diabetes Mellitus, Type 1 Hyperglycemia Hypoglycemic Agents Hypoglycemia Humans Artificial Intelligence
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Impact of machine learning-based coronary computed tomography angiography fractional flow reserve on treatment decisions and clinical outcomes in patients with suspected coronary artery disease.

European radiology May 28, 2020
OBJECTIVES: This study investigated the impact of machine learning (ML)-based fractional flow reserve derived from computed tomography (FFR) compared to invasive coronary angiography (ICA) for therapeutic decision-making and patient outcome in patien...
Decision Making Predictive Value of Tests Coronary Angiography Coronary Artery Disease Disease Management Computed Tomography Angiography Fractional Flow Reserve, Myocardial Female Male Middle Aged Severity of Illness Index Humans Artificial Intelligence Machine Learning Retrospective Studies
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Machine Learning (ML) based-method applied in recurrent pregnancy loss (RPL) patients diagnostic work-up: a potential innovation in common clinical practice.

Scientific reports May 14, 2020
RPL is a very debated condition, in which many issues concerning definition, etiological factors to investigate or therapies to apply are still controversial. ML could help clinicians to reach an objectiveness in RPL classification and access to care...
Humans Adult Middle Aged Adolescent Support Vector Machine Clinical Decision-Making Disease Management Machine Learning Pregnancy Abortion, Habitual Algorithms Female Biomarkers Young Adult
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A Machine Learning Approach to Management of Heart Failure Populations.

JACC. Heart failure May 6, 2020
BACKGROUND: Heart failure is a prevalent, costly disease for which new value-based payment models demand optimized population management strategies.
Humans Machine Learning ROC Curve United States Population Surveillance Morbidity Aged, 80 and over Heart Failure Retrospective Studies Male Disease Management Female Middle Aged Aged Risk Assessment
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Impact of machine-learning CT-derived fractional flow reserve for the diagnosis and management of coronary artery disease in the randomized CRESCENT trials.

European radiology Mar 12, 2020
OBJECTIVE: To determine the potential impact of on-site CT-derived fractional flow reserve (CT-FFR) on the diagnostic efficiency and effectiveness of coronary CT angiography (CCTA) in patients with obstructive coronary artery disease (CAD) on CCTA.
Middle Aged Hemodynamics Cohort Studies Coronary Angiography Female Aged Male Computed Tomography Angiography Percutaneous Coronary Intervention Coronary Stenosis Humans Coronary Artery Disease Fractional Flow Reserve, Myocardial Machine Learning Disease Management Retrospective Studies Cardiac Catheterization Tomography, X-Ray Computed
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Clinical management of sepsis can be improved by artificial intelligence: no.

Intensive care medicine Feb 3, 2020
Sepsis Decision Support Systems, Clinical Disease Management Quality of Health Care Humans Artificial Intelligence
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Clinical management of sepsis can be improved by artificial intelligence: yes.

Intensive care medicine Dec 13, 2019
Decision Support Systems, Clinical Disease Management Humans Artificial Intelligence Sepsis
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