AIMC Topic: Respiratory Tract Diseases

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Lightweight Hybrid Deep Learning Models for Accurate Classification of Respiratory Conditions from Raw Lung Sounds.

Journal of medical systems
In recent years, progress in artificial intelligence, particularly in the realm of deep learning, has resulted in substantial enhancements in the diagnosis of various medical conditions. This study introduces a framework that leverages multiple light...

Mapping respiratory health digital interventions in South and Southeast Asia: a scoping review.

Journal of global health
BACKGROUND: The growing burden of respiratory disease, particularly in Asia, where mortality is higher and awareness and policy engagement lag, could be mitigated through rapidly advancing digital health tools that offer opportunities for improved ma...

Artificial intelligence platform to predict children's hospital care for respiratory disease using clinical, pollution, and climatic factors.

Journal of global health
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
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
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
. 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
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...

An accurate prediction for respiratory diseases using deep learning on bronchoscopy diagnosis images.

Journal of advanced research
INTRODUCTION: Bronchoscopy is of great significance in diagnosing and treating respiratory illness. Using deep learning, a diagnostic system for bronchoscopy images can improve the accuracy of tracheal, bronchial, and pulmonary disease diagnoses for ...

Next-generation pediatric care: nanotechnology-based and AI-driven solutions for cardiovascular, respiratory, and gastrointestinal disorders.

World journal of pediatrics : WJP
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
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...