[HTML][HTML] Optimized ensemble learning approach with explainable AI for improved heart disease prediction
Recent advances in machine learning (ML) have shown great promise in detecting heart
disease. However, to ensure the clinical adoption of ML models, they must not only be …
disease. However, to ensure the clinical adoption of ML models, they must not only be …
A topic modeling‐based bibliometric exploration of automatic summarization research
The surge in text data has driven extensive research into developing diverse automatic
summarization approaches to effectively handle vast textual information. There are several …
summarization approaches to effectively handle vast textual information. There are several …
[HTML][HTML] Health Risk Assessment Using Machine Learning: Systematic Review
SE Abhadiomhen, EO Nzeakor, K Oyibo - Electronics, 2024 - mdpi.com
According to the World Health Organization, chronic illnesses account for over 70% of
deaths globally, underscoring the need for effective health risk assessment (HRA). While …
deaths globally, underscoring the need for effective health risk assessment (HRA). While …
Kacq-dcnn: Uncertainty-aware interpretable kolmogorov-arnold classical-quantum dual-channel neural network for heart disease detection
Heart failure remains a major global health challenge, contributing significantly to the 17.8
million annual deaths from cardiovascular disease, highlighting the need for improved …
million annual deaths from cardiovascular disease, highlighting the need for improved …
Enhanced heart disease prediction through hybrid CNN-TLBO-GA optimization: a comparative study with conventional CNN and optimized CNN using FPO algorithm
RP Ram Kumar, S Raju, E Annapoorna… - Cogent …, 2024 - Taylor & Francis
Cardiovascular diseases (CD), or heart diseases (HD), lead to approximately 17.9 million
deaths each year, constituting 32% of global fatalities. Early detection and appropriate …
deaths each year, constituting 32% of global fatalities. Early detection and appropriate …
Text Sentiment Analysis of Douban Film Short Comments Based on BERT-CNN-BiLSTM-Att Model
A He, M Abisado - IEEE Access, 2024 - ieeexplore.ieee.org
To solve the problems of polysemy and feature extraction in the text sentiment analysis
process, a BERT-CNN-BiLSTM-Att hybrid model has been proposed for text sentiment …
process, a BERT-CNN-BiLSTM-Att hybrid model has been proposed for text sentiment …
Stronger Baseline Models--A Key Requirement for Aligning Machine Learning Research with Clinical Utility
Machine Learning (ML) research has increased substantially in recent years, due to the
success of predictive modeling across diverse application domains. However, well-known …
success of predictive modeling across diverse application domains. However, well-known …
Predictive Modeling for Diabetes Using GraphLIME
The purpose of this paper is to present a detailed investigation of the advantages of
employing GraphLIME (Local Interpretable Model Explanations for Graph Neural Networks) …
employing GraphLIME (Local Interpretable Model Explanations for Graph Neural Networks) …
[HTML][HTML] Heart disease prediction using autoencoder and DenseNet architecture
NS Alghamdi, M Zakariah, A Shankar… - Egyptian Informatics …, 2024 - Elsevier
Heart disease continues to be a prominent cause of death globally, emphasizing the critical
requirement for precise prediction techniques and prompt therapies. This research presents …
requirement for precise prediction techniques and prompt therapies. This research presents …
A smart CardioSenseNet framework with advanced data processing models for precise heart disease detection
R Subathra, V Sumathy - Computers in Biology and Medicine, 2025 - Elsevier
Heart diseases remain one of the leading causes of death worldwide. As a result, early and
accurate diagnostics have become an urgent need for treatment and management. Most of …
accurate diagnostics have become an urgent need for treatment and management. Most of …