AIMC Topic: Respiratory Tract Diseases
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Artificial intelligence platform to predict children's hospital care for respiratory disease using clinical, pollution, and climatic factors.
Journal of global health
Jul 21, 2025
BACKGROUND: Hospitals and health care systems may benefit from artificial intelligence (AI) and big data to analyse clinical information combined with external sources. Machine learning, a subset of AI, uses algorithms trained on data to generate pre...
The association of life's essential 8 with prevalence of chronic respiratory diseases in adults: insights from NHANES 2007-2018.
BMC pulmonary medicine
Jul 9, 2025
OBJECTIVE: Chronic respiratory diseases (CRDs) and cardiovascular diseases (CVD) share common risk factors and frequently co-occur, leading to poorer outcomes. Life's Essential 8 (LE8), a novel metric for cardiovascular health, may provide insights i...
Advancing respiratory disease diagnosis: A deep learning and vision transformer-based approach with a novel X-ray dataset.
Computers in biology and medicine
Jun 9, 2025
With the increasing prevalence of respiratory diseases such as pneumonia and COVID-19, timely and accurate diagnosis is critical. This paper makes significant contributions to the field of respiratory disease classification by utilizing X-ray images ...
Self-critical strategy adjustment based artificial intelligence method in generating diagnostic reports of respiratory diseases.
Physiological measurement
Jan 29, 2025
. Humanity faces many health challenges, among which respiratory diseases are one of the leading causes of human death. Existing AI-driven pre-diagnosis approaches can enhance the efficiency of diagnosis but still face challenges. For example, single...
Machine learning analysis of CD4+ T cell gene expression in diverse diseases: insights from cancer, metabolic, respiratory, and digestive disorders.
Cancer genetics
Dec 22, 2024
CD4 T cells play a pivotal role in the immune system, particularly in adaptive immunity, by orchestrating and enhancing immune responses. CD4 T cell-related immune responses exhibit diverse characteristics in different diseases. This study utilizes g...
Next-generation pediatric care: nanotechnology-based and AI-driven solutions for cardiovascular, respiratory, and gastrointestinal disorders.
World journal of pediatrics : WJP
Aug 28, 2024
BACKGROUND: Global pediatric healthcare reveals significant morbidity and mortality rates linked to respiratory, cardiac, and gastrointestinal disorders in children and newborns, mostly due to the complexity of therapeutic management in pediatrics an...
Predicting hospital admissions for upper respiratory tract complaints: An artificial neural network approach integrating air pollution and meteorological factors.
Environmental monitoring and assessment
Jul 24, 2024
This study uses artificial neural networks (ANNs) to examine the intricate relationship between air pollutants, meteorological factors, and respiratory disorders. The study investigates the correlation between hospital admissions for respiratory dise...
Improved pediatric ICU mortality prediction for respiratory diseases: machine learning and data subdivision insights.
Respiratory research
May 23, 2024
The growing concern of pediatric mortality demands heightened preparedness in clinical settings, especially within intensive care units (ICUs). As respiratory-related admissions account for a substantial portion of pediatric illnesses, there is a pre...
Respiratory Diseases Diagnosis Using Audio Analysis and Artificial Intelligence: A Systematic Review.
Sensors (Basel, Switzerland)
Feb 10, 2024
Respiratory diseases represent a significant global burden, necessitating efficient diagnostic methods for timely intervention. Digital biomarkers based on audio, acoustics, and sound from the upper and lower respiratory system, as well as the voice,...
Artificial intelligence can dynamically adjust strategies for auxiliary diagnosing respiratory diseases and analyzing potential pathological relationships.
Journal of breath research
Aug 25, 2023
Respiratory diseases are one of the leading causes of human death and exacerbate the global burden of non-communicable diseases. Finding a method to assist clinicians pre-diagnose these diseases is an urgent task. Existing artificial intelligence-bas...
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