[HTML][HTML] Artificial intelligence and machine learning in chronic airway diseases: focus on asthma and chronic obstructive pulmonary disease

Y Feng, Y Wang, C Zeng, H Mao - International journal of medical …, 2021 - ncbi.nlm.nih.gov
Chronic airway diseases are characterized by airway inflammation, obstruction, and
remodeling and show high prevalence, especially in developing countries. Among them …

[HTML][HTML] ResNet-50 vs VGG-19 vs training from scratch: A comparative analysis of the segmentation and classification of Pneumonia from chest X-ray images

AV Ikechukwu, S Murali, R Deepu… - Global Transitions …, 2021 - Elsevier
In medical imaging, segmentation plays a vital role towards the interpretation of X-ray
images where salient features are extracted with the help of image segmentation. Without …

Automated detection of airflow obstructive diseases: a systematic review of the last decade (2013-2022)

S Xu, RC Deo, J Soar, PD Barua, O Faust… - Computer Methods and …, 2023 - Elsevier
Abstract Background and Objective Obstructive airway diseases, including asthma and
Chronic Obstructive Pulmonary Disease (COPD), are two of the most common chronic …

[HTML][HTML] Acute exacerbation of a chronic obstructive pulmonary disease prediction system using wearable device data, machine learning, and deep learning …

CT Wu, GH Li, CT Huang, YC Cheng… - JMIR mHealth and …, 2021 - mhealth.jmir.org
Background: The World Health Organization has projected that by 2030, chronic obstructive
pulmonary disease (COPD) will be the third-leading cause of mortality and the seventh …

[HTML][HTML] Utilization of decision tree algorithms for supporting the prediction of intensive care unit admission of myasthenia gravis: a machine learning-based approach

CC Chang, JH Yeh, HC Chiu, YM Chen… - Journal of Personalized …, 2022 - mdpi.com
Myasthenia gravis (MG), an acquired autoimmune-related neuromuscular disorder that
causes muscle weakness, presents with varying severity, including myasthenic crisis (MC) …

[HTML][HTML] Explainable machine learning model for predicting first-time acute exacerbation in patients with chronic obstructive pulmonary disease

CT Kor, YR Li, PR Lin, SH Lin, BY Wang… - Journal of personalized …, 2022 - mdpi.com
Background: The study developed accurate explainable machine learning (ML) models for
predicting first-time acute exacerbation of chronic obstructive pulmonary disease (COPD …

[HTML][HTML] Forecast the exacerbation in patients of chronic obstructive pulmonary disease with clinical indicators using machine learning techniques

A Hussain, HE Choi, HJ Kim, S Aich, M Saqlain… - Diagnostics, 2021 - mdpi.com
Preventing exacerbation and seeking to determine the severity of the disease during the
hospitalization of chronic obstructive pulmonary disease (COPD) patients is a crucial global …

[HTML][HTML] Simplified decision-tree algorithm to predict falls for community-dwelling older adults

K Makino, S Lee, S Bae, I Chiba, K Harada… - Journal of clinical …, 2021 - mdpi.com
The present study developed a simplified decision-tree algorithm for fall prediction with
easily measurable predictors using data from a longitudinal cohort study: 2520 community …

[HTML][HTML] Prediction of patients with COVID-19 requiring intensive care: A cross-sectional study based on machine-learning approach from Iran

G Sabetian, A Azimi, A Kazemi, B Hoseini… - Indian Journal of …, 2022 - ncbi.nlm.nih.gov
Background Prioritizing the patients requiring intensive care may decrease the fatality of
coronavirus disease-2019 (COVID-19). Aims and objectives To develop, validate, and …

A precision health service for chronic diseases: development and cohort study using wearable device, machine learning, and deep learning

CT Wu, SM Wang, YE Su, TT Hsieh… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
This paper presents an integrated and scalable precision health service for health promotion
and chronic disease prevention. Continuous real-time monitoring of lifestyle and …