Artificial intelligence for cardiovascular disease risk assessment in personalised framework: a sco** review
Background The field of precision medicine endeavors to transform the healthcare industry
by advancing individualised strategies for diagnosis, treatment modalities, and predictive …
by advancing individualised strategies for diagnosis, treatment modalities, and predictive …
Deep-learning-based 3D super-resolution CT radiomics model: Predict the possibility of the micropapillary/solid component of lung adenocarcinoma
X **ng, L Li, M Sun, J Yang, X Zhu, F Peng, J Du… - Heliyon, 2024 - cell.com
Objective Invasive lung adenocarcinoma (ILA) with micropapillary (MPP)/solid (SOL)
components has a poor prognosis. Preoperative identification is essential for decision …
components has a poor prognosis. Preoperative identification is essential for decision …
[HTML][HTML] UltraAIGenomics: Artificial Intelligence-Based Cardiovascular Disease Risk Assessment by Fusion of Ultrasound-Based Radiomics and Genomics Features …
Cardiovascular disease (CVD) diagnosis and treatment are challenging since symptoms
appear late in the disease's progression. Despite clinical risk scores, cardiac event …
appear late in the disease's progression. Despite clinical risk scores, cardiac event …
Deep learning approach for cardiovascular disease risk stratification and survival analysis on a Canadian cohort
The quantification of carotid plaque has been routinely used to predict cardiovascular risk in
cardiovascular disease (CVD) and coronary artery disease (CAD). To determine how well …
cardiovascular disease (CVD) and coronary artery disease (CAD). To determine how well …
Generative Adversarial Network-based Deep Learning Framework for Cardiovascular Disease Risk Prediction
Early risk assessment is essential since cardiovascular disease (CVD) is a significant
healthcare burden. Earlier assessment methods either employed machine learning (ML) …
healthcare burden. Earlier assessment methods either employed machine learning (ML) …
A Novel Approach for the Detection and Severity Grading of Chronic Obstructive Pulmonary Disease Based on Transformed Volumetric Capnography
Chronic Obstructive Pulmonary Disease (COPD), as the third leading cause of death
worldwide, is a major global health issue. The early detection and grading of COPD are …
worldwide, is a major global health issue. The early detection and grading of COPD are …
[PDF][PDF] Stroke Risk Factor Prediction Using Machine Learning Techniques: A Systematic Review
This review addresses the global challenge of stroke, a leading cause of disability and
mortality. The unpredictability and severe impact of stroke necessitate advanced prediction …
mortality. The unpredictability and severe impact of stroke necessitate advanced prediction …
The Role of AI in Enhancing Healthcare Access and Service Quality in Resource-Limited Settings
R Farhat, ARA Malik, AH Sheikh… - International Journal of …, 2024 - lamintang.org
Abstract The integration of Artificial Intelligence (AI) in healthcare has become a critical
factor in improving healthcare delivery, particularly in resource-limited environments. In …
factor in improving healthcare delivery, particularly in resource-limited environments. In …
Carotid Artery Ultrasound Image-Based Cardiovascular Risk Prediction using Deep Learning
MM Vila Muñoz - 2024 - diposit.ub.edu
[eng] Cardiovascular Diseases (CVDs), the leading cause of death in developed countries,
often involve atherosclerosis, which is a chronic inflammatory thickening of the inner artery …
often involve atherosclerosis, which is a chronic inflammatory thickening of the inner artery …
[HTML][HTML] An Artificial Intelligence-Based Non-Invasive Approach for Cardiovascular Disease Risk Stratification in Obstructive Sleep Apnea Patients: A Narrative Review
Background: Obstructive sleep apnea (OSA) is a severe condition associated with numerous
cardiovascular complications, including heart failure. The complex biological and …
cardiovascular complications, including heart failure. The complex biological and …