AIMC Topic: Acute Disease

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Current imaging of PE and emerging techniques: is there a role for artificial intelligence?

Clinical imaging May 10, 2022
Acute pulmonary embolism (PE) is a critical, potentially life-threatening finding on contrast-enhanced cross-sectional chest imaging. Timely and accurate diagnosis of thrombus acuity and extent directly influences patient management, and outcomes. Te...
Cross-Sectional Studies Diagnostic Imaging Acute Disease Pulmonary Embolism Humans Artificial Intelligence
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Assessing central serous chorioretinopathy with deep learning and multiple optical coherence tomography images.

Scientific reports Feb 3, 2022
Central serous chorioretinopathy (CSC) is one of the most common macular diseases that can reduce the quality of life of patients. This study aimed to build a deep learning-based classification model using multiple spectral domain optical coherence t...
Humans Chronic Disease Female Tomography, Optical Coherence Aged Acute Disease Adult Retina Male Case-Control Studies Middle Aged Deep Learning Diagnosis, Differential Image Interpretation, Computer-Assisted Central Serous Chorioretinopathy
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Early prediction of severe acute pancreatitis using machine learning.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.] Oct 16, 2021
BACKGROUND: Acute pancreatitis (AP) is one of the most common causes of gastrointestinal-related hospitalizations in the United States. Severe AP (SAP) is associated with a mortality rate of nearly 30% and is distinguished from milder forms of AP. Ri...
Female Aged Aged, 80 and over Adult Humans Machine Learning Prognosis Retrospective Studies Pancreatitis Male Adolescent Middle Aged ROC Curve Severity of Illness Index Predictive Value of Tests Acute Disease
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Deep Learning and Risk Assessment in Acute Pulmonary Embolism.

Radiology Sep 28, 2021
Deep Learning Venous Thrombosis Acute Disease Pulmonary Embolism Humans Risk Assessment
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Efficiency of a deep learning-based artificial intelligence diagnostic system in spontaneous intracerebral hemorrhage volume measurement.

BMC medical imaging Aug 13, 2021
BACKGROUND: Accurate measurement of hemorrhage volume is critical for both the prediction of prognosis and the selection of appropriate clinical treatment after spontaneous intracerebral hemorrhage (ICH). This study aimed to evaluate the performance ...
Cerebral Intraventricular Hemorrhage Adult Male Middle Aged Diagnosis, Computer-Assisted Deep Learning Cerebral Hemorrhage Acute Disease Retrospective Studies Tomography, X-Ray Computed Female Aged Humans
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Detecting neonatal acute bilirubin encephalopathy based on T1-weighted MRI images and learning-based approaches.

BMC medical imaging Jun 22, 2021
BACKGROUND: Neonatal hyperbilirubinemia is a common clinical condition that requires medical attention in newborns, which may develop into acute bilirubin encephalopathy with a significant risk of long-term neurological deficits. The current clinical...
Hyperbilirubinemia, Neonatal Kernicterus Male Deep Learning Magnetic Resonance Imaging Diagnosis, Differential Humans Acute Disease Retrospective Studies Chi-Square Distribution Female Subthalamic Nucleus Infant, Newborn Globus Pallidus
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CKLF and IL1B transcript levels at diagnosis are predictive of relapse in children with pre-B-cell acute lymphoblastic leukaemia.

British journal of haematology Feb 23, 2021
Disease relapse is the greatest cause of treatment failure in paediatric B-cell acute lymphoblastic leukaemia (B-ALL). Current risk stratifications fail to capture all patients at risk of relapse. Herein, we used a machine-learning approach to identi...
Precursor B-Cell Lymphoblastic Leukemia-Lymphoma MARVEL Domain-Containing Proteins Treatment Failure Chemokines Recurrence Male Risk Assessment Infant Transcriptome Humans Machine Learning Female Predictive Value of Tests Adolescent Interleukin-1beta Child, Preschool Acute Disease Child Survival Analysis
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Suspected Acute Pulmonary Embolism: Gestalt, Scoring Systems, and Artificial Intelligence.

Seminars in respiratory and critical care medicine Feb 16, 2021
Pulmonary embolism (PE) remains a diagnostic challenge in 2021. As the pathology is potentially fatal and signs and symptoms are nonspecific, further investigations are classically required. Based on the Bayesian approach, clinical probability became...
Acute Disease Bayes Theorem Pulmonary Embolism Humans Angiography Artificial Intelligence
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Predictive Analytics for Care and Management of Patients With Acute Diseases: Deep Learning-Based Method to Predict Crucial Complication Phenotypes.

Journal of medical Internet research Feb 12, 2021
BACKGROUND: Acute diseases present severe complications that develop rapidly, exhibit distinct phenotypes, and have profound effects on patient outcomes. Predictive analytics can enhance physicians' care and management of patients with acute diseases...
Humans Neural Networks, Computer Research Design Phenotype Deep Learning Acute Disease
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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...
Triage Female Natural Language Processing Acute Disease Humans Male Emergency Service, Hospital Early Diagnosis Algorithms Middle Aged Gastrointestinal Hemorrhage Electronic Health Records Risk Assessment Clinical Decision Rules
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