Statistical analysis of design aspects of various YOLO-based deep learning models for object detection
Object detection is a critical and complex problem in computer vision, and deep neural
networks have significantly enhanced their performance in the last decade. There are two …
networks have significantly enhanced their performance in the last decade. There are two …
Enhancing heart disease prediction accuracy through machine learning techniques and optimization
N Chandrasekhar, S Peddakrishna - Processes, 2023 - mdpi.com
In the medical domain, early identification of cardiovascular issues poses a significant
challenge. This study enhances heart disease prediction accuracy using machine learning …
challenge. This study enhances heart disease prediction accuracy using machine learning …
Advanced machine learning techniques for cardiovascular disease early detection and diagnosis
NA Baghdadi, SM Farghaly Abdelaliem, A Malki… - Journal of Big Data, 2023 - Springer
The identification and prognosis of the potential for developing Cardiovascular Diseases
(CVD) in healthy individuals is a vital aspect of disease management. Accessing the …
(CVD) in healthy individuals is a vital aspect of disease management. Accessing the …
A pharmaceutical paradigm for cardiovascular composite risk assessment using novel radiogenomics risk predictors in precision explainable artificial intelligence …
Background: Cardiovascular disease (CVD) is challenging to diagnose and treat since
symptoms appear late during the progression of atherosclerosis. Conventional risk factors …
symptoms appear late during the progression of atherosclerosis. Conventional risk factors …
A software framework for predicting the maize yield using modified multi-layer perceptron
S Ahmed - Sustainability, 2023 - mdpi.com
Predicting crop yields is one of agriculture's most challenging issues. It is crucial in making
national, provincial, and regional choices and estimates the government to meet the food …
national, provincial, and regional choices and estimates the government to meet the food …
Diabetes prediction using Shapley additive explanations and DSaaS over machine learning classifiers: a novel healthcare paradigm
Technologies like cloud computing, Artificial Intelligence (AI), and Machine intelligence
technologies must combine to accomplish computational intelligence. To deliberate the …
technologies must combine to accomplish computational intelligence. To deliberate the …
[HTML][HTML] Leveraging mobile phone sensors, machine learning, and explainable artificial intelligence to predict imminent same-day binge-drinking events to support just …
Background Digital just-in-time adaptive interventions can reduce binge-drinking events
(BDEs; consuming≥ 4 drinks for women and≥ 5 drinks for men per occasion) in young …
(BDEs; consuming≥ 4 drinks for women and≥ 5 drinks for men per occasion) in young …
An automatic ensemble machine learning for wheat yield prediction in Africa
Wheat is an essential crop for food security in North Africa. However, it's productivity is
limited by several factors, among them climate change effects. Predicting wheat yield on a …
limited by several factors, among them climate change effects. Predicting wheat yield on a …
[HTML][HTML] Towards explainability in artificial intelligence frameworks for heartcare: A comprehensive survey
Artificial Intelligence is extensively applied in heartcare to analyze patient data, detect
anomalies, and provide personalized treatment recommendations, ultimately improving …
anomalies, and provide personalized treatment recommendations, ultimately improving …
Cardiovascular disease detection using a novel stack-based ensemble classifier with aggregation layer, DOWA operator, and feature transformation
Due to their widespread prevalence and impact on quality of life, cardiovascular diseases
(CVD) pose a considerable global health burden. Early detection and intervention can …
(CVD) pose a considerable global health burden. Early detection and intervention can …