Predictive models for personalized asthma attacks based on patient's biosignals and environmental factors: a systematic review
Background Asthma is a chronic disease that exacerbates due to various risk factors,
including the patient's biosignals and environmental conditions. It is affecting on average 7 …
including the patient's biosignals and environmental conditions. It is affecting on average 7 …
Diagnosis of asthma disease and the levels using forward chaining and certainty factor
M Irfan, P Alkautsar, AR Atmadja… - Jurnal RESTI (Rekayasa …, 2022 - jurnal.iaii.or.id
Asthma disease is a major global health issue that affects at least 300 million people
worldwide. Even for clinicians working in emergency rooms, predicting the severity of …
worldwide. Even for clinicians working in emergency rooms, predicting the severity of …
Integrated platform and response system for healthcare using Alexa
MV Sakthive, MPV Kesaven, MJM William… - International Journal of …, 2019 - ijccts.org
This paper presents a Healthcare system by providing a virtual personal assistance using
the Amazon Alexa. Amazon Alexa is an application program that understands voice …
the Amazon Alexa. Amazon Alexa is an application program that understands voice …
Smart healthcare framework for asthma attack prediction and prevention
Smart healthcare is one of the most exciting applications introduced to provide better
disease diagnosis and prediction tools. Recent studies introduced various disease …
disease diagnosis and prediction tools. Recent studies introduced various disease …
Predicting lung healthiness risk scores to identify probability of an asthma attack
Q Do, A Doig, TC Son, J Chaudri - Procedia Computer Science, 2019 - Elsevier
For asthma, monitoring of symptoms and progression of the disease while avoiding triggers
and minimizing the frequency of attacks are the main objectives of care. Tracking and …
and minimizing the frequency of attacks are the main objectives of care. Tracking and …
Developing Model-Agnostic Meta-Learning Enabled Lightbgm Model Asthma Level Prediction in Smart Healthcare Modeling
Millions of people across the world suffer from the chronic respiratory condition known as
asthma. Predicting the severity of asthma based on a variety of personal and environmental …
asthma. Predicting the severity of asthma based on a variety of personal and environmental …
Asthma diagnosis using neuro-fuzzy techniques
A Ghosh, N Rahman, N Awadalla… - 2020 Advances in …, 2020 - ieeexplore.ieee.org
Asthma is one of the most common causes of respiratory diseases. By taking into
consideration the possibility of this disease worsening over time and its negative impact on …
consideration the possibility of this disease worsening over time and its negative impact on …
Environment-Based Asthma Trigger Detection (ATD)
S Chourasiya, L Panchal, M Dangra… - ICT Systems and …, 2022 - Springer
More than 300 million people worldwide suffer from asthma, and around 2 million people die
each year as a result of asthma attacks. Asthma can be started and exacerbated by many …
each year as a result of asthma attacks. Asthma can be started and exacerbated by many …
Reinforcement learning framework to identify cause of diseases-predicting asthma attack case
Asthma attack prediction is a highly challenging problem because of the dynamic and multi-
factor nature of its etiology. Disease severity level, physiological measurements, patient …
factor nature of its etiology. Disease severity level, physiological measurements, patient …
Detecting a respiratory abnormality using a convolution, and applications thereof
IM McLane - US Patent 10,709,353, 2020 - Google Patents
Embodiments disclosed herein improve digital stethoscopes and their application and
operation. A first method detects of a respiratory abnormality using a convolution. A second …
operation. A first method detects of a respiratory abnormality using a convolution. A second …