Predictive models for personalized asthma attacks based on patient's biosignals and environmental factors: a systematic review

ET Alharbi, F Nadeem, A Cherif - BMC Medical Informatics and Decision …, 2021 - Springer
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 …

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 …

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 …

Smart healthcare framework for asthma attack prediction and prevention

E Alharbi, F Nadeem, A Cherif - 2021 National Computing …, 2021 - ieeexplore.ieee.org
Smart healthcare is one of the most exciting applications introduced to provide better
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 …

Developing Model-Agnostic Meta-Learning Enabled Lightbgm Model Asthma Level Prediction in Smart Healthcare Modeling

S Yadav, H Sehrawat, V Jaglan, Y Singh… - … Computing: Practice and …, 2024 - scpe.org
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 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 …

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 …

Reinforcement learning framework to identify cause of diseases-predicting asthma attack case

Q Do, S Tran, A Doig - … Conference on Big Data (Big Data), 2019 - ieeexplore.ieee.org
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 …

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 …