AIMC Topic: Disease Susceptibility

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Spatial prediction of human brucellosis susceptibility using an explainable optimized adaptive neuro fuzzy inference system.

Acta tropica Nov 30, 2024
Brucellosis, a zoonotic disease caused by Brucella bacteria, poses significant risks to human, livestock, and wildlife health, alongside economic losses from livestock morbidity and mortality. This study improves Human Brucellosis Susceptibility Mapp...
Fuzzy Logic Iran Spatial Analysis Disease Susceptibility Brucella Humans Algorithms Animals Brucellosis
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Managing spatio-temporal heterogeneity of susceptibles by embedding it into an homogeneous model: A mechanistic and deep learning study.

PLoS computational biology Sep 30, 2024
Accurate prediction of epidemics is pivotal for making well-informed decisions for the control of infectious diseases, but addressing heterogeneity in the system poses a challenge. In this study, we propose a novel modelling framework integrating the...
Deep Learning Humans China Computational Biology Disease Susceptibility Epidemiological Models Neural Networks, Computer COVID-19 SARS-CoV-2 Spatio-Temporal Analysis
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Development and validation of a practical machine-learning triage algorithm for the detection of patients in need of critical care in the emergency department.

Scientific reports Dec 15, 2021
Identifying critically ill patients is a key challenge in emergency department (ED) triage. Mis-triage errors are still widespread in triage systems around the world. Here, we present a machine learning system (MLS) to assist ED triage officers bette...
Humans Machine Learning ROC Curve Triage Aged Area Under Curve Odds Ratio Algorithms Adult Critical Care Emergency Service, Hospital Disease Susceptibility Critical Illness Disease Management Male Clinical Decision-Making Middle Aged Female
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Machine learning models for screening carotid atherosclerosis in asymptomatic adults.

Scientific reports Nov 15, 2021
Carotid atherosclerosis (CAS) is a risk factor for cardiovascular and cerebrovascular events, but duplex ultrasonography isn't recommended in routine screening for asymptomatic populations according to medical guidelines. We aim to develop machine le...
Female Aged Male Middle Aged Humans Machine Learning Biomarkers Disease Susceptibility Asymptomatic Diseases Carotid Artery Diseases ROC Curve Models, Theoretical Mass Screening Support Vector Machine
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Risk factor assessments of temporomandibular disorders via machine learning.

Scientific reports Oct 5, 2021
This study aimed to use artificial intelligence to determine whether biological and psychosocial factors, such as stress, socioeconomic status, and working conditions, were major risk factors for temporomandibular disorders (TMDs). Data were retrieve...
Disease Susceptibility Aged Adult Male Middle Aged Public Health Surveillance Temporomandibular Joint Disorders Odds Ratio Risk Assessment Models, Theoretical Machine Learning Republic of Korea Female Risk Factors Humans Artificial Intelligence
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Machine learning risk prediction model for acute coronary syndrome and death from use of non-steroidal anti-inflammatory drugs in administrative data.

Scientific reports Sep 15, 2021
Our aim was to investigate the usefulness of machine learning approaches on linked administrative health data at the population level in predicting older patients' one-year risk of acute coronary syndrome and death following the use of non-steroidal ...
Proportional Hazards Models Disease Susceptibility Comorbidity ROC Curve Models, Theoretical Australia Cause of Death Disease Management Acute Coronary Syndrome Anti-Inflammatory Agents, Non-Steroidal Area Under Curve Risk Factors Prognosis Male Humans Female Machine Learning Risk Assessment
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Uncovering cancer vulnerabilities by machine learning prediction of synthetic lethality.

Molecular cancer Aug 28, 2021
BACKGROUND: Synthetic lethality describes a genetic interaction between two perturbations, leading to cell death, whereas neither event alone has a significant effect on cell viability. This concept can be exploited to specifically target tumor cells...
Humans Machine Learning Neoplasms Gene Expression Profiling Genetic Predisposition to Disease Computational Biology Models, Biological Cell Line, Tumor Genomics Disease Susceptibility Synthetic Lethal Mutations
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Prediction of venous thromboembolism with machine learning techniques in young-middle-aged inpatients.

Scientific reports Jun 18, 2021
Accumulating studies appear to suggest that the risk factors for venous thromboembolism (VTE) among young-middle-aged inpatients are different from those among elderly people. Therefore, the current prediction models for VTE are not applicable to you...
Area Under Curve Venous Thromboembolism Disease Management Disease Susceptibility Middle Aged Adolescent Support Vector Machine Inpatients Prognosis Female Young Adult Adult Male Humans Machine Learning
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Machine Learning Identifies Complicated Sepsis Course and Subsequent Mortality Based on 20 Genes in Peripheral Blood Immune Cells at 24 H Post-ICU Admission.

Frontiers in immunology Feb 22, 2021
A complicated clinical course for critically ill patients admitted to the intensive care unit (ICU) usually includes multiorgan dysfunction and subsequent death. Owing to the heterogeneity, complexity, and unpredictability of the disease progression,...
Reproducibility of Results Humans Time Factors Critical Care Gene Expression Profiling Machine Learning Databases, Genetic Disease Susceptibility Transcriptome Hospital Mortality Biomarkers Leukocytes Chromosome Mapping Sepsis ROC Curve Intensive Care Units Computational Biology
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Towards a Precision Medicine Approach Based on Machine Learning for Tailoring Medical Treatment in Alkaptonuria.

International journal of molecular sciences Jan 26, 2021
ApreciseKUre is a multi-purpose digital platform facilitating data collection, integration and analysis for patients affected by Alkaptonuria (AKU), an ultra-rare autosomal recessive genetic disease. It includes genetic, biochemical, histopathologica...
Precision Medicine Quality of Life Models, Theoretical Disease Management Humans Machine Learning Algorithms Databases, Factual Disease Susceptibility Alkaptonuria
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