Copertina

A Multi-target Bayesian Transformer Framework for Predicting Cardiovascular Disease Biomarkers during Pandemics

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Inekwe, Trusting, Mkandawire, Winnie, Agu, Emmanuel, Colubri, Andres
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Explainable Machine Learning Framework for Cardiovascular Disease Diagnosis and Prognosis
di: Sourov, Md. Emon Akter, et al.
Pubblicazione: (2025)

HyCARD-Net: A Synergistic Hybrid Intelligence Framework for Cardiovascular Disease Diagnosis
di: Gupta, Rajan Das, et al.
Pubblicazione: (2026)

Fuzzy Rule based Intelligent Cardiovascular Disease Prediction using Complex Event Processing
di: Kumar, Shashi Shekhar, et al.
Pubblicazione: (2024)

BioCOMPASS: Integrating Biomarkers into Transformer-Based Immunotherapy Response Prediction
di: Hashim, Sayed, et al.
Pubblicazione: (2026)

Adaptable Cardiovascular Disease Risk Prediction from Heterogeneous Data using Large Language Models
di: Lübeck, Frederike, et al.
Pubblicazione: (2025)

Multi-modal Multi-kernel Graph Learning for Autism Prediction and Biomarker Discovery
di: Liu, Jin, et al.
Pubblicazione: (2023)

Rethinking Spatio-Temporal Transformer for Traffic Prediction:Multi-level Multi-view Augmented Learning Framework
di: Lin, Jiaqi, et al.
Pubblicazione: (2024)

Variational Routing: A Scalable Bayesian Framework for Calibrated Mixture-of-Experts Transformers
di: Li, Albus Yizhuo, et al.
Pubblicazione: (2026)

Versatile Cardiovascular Signal Generation with a Unified Diffusion Transformer
di: Chen, Zehua, et al.
Pubblicazione: (2025)

Kalman Bayesian Transformer
di: Jing, Haoming, et al.
Pubblicazione: (2025)

Chinese Stock Prediction Based on a Multi-Modal Transformer Framework: Macro-Micro Information Fusion
di: AI, Lumen, et al.
Pubblicazione: (2025)

Research on Early Warning Model of Cardiovascular Disease Based on Computer Deep Learning
di: Hu, Yuxiang, et al.
Pubblicazione: (2024)

Residual GRU+MHSA: A Lightweight Hybrid Recurrent Attention Model for Cardiovascular Disease Detection
di: Dash, Tejaswani, et al.
Pubblicazione: (2025)

The Bayesian Geometry of Transformer Attention
di: Agarwal, Naman, et al.
Pubblicazione: (2025)

Predicting Heart Failure with Attention Learning Techniques Utilizing Cardiovascular Data
di: Haque, Ershadul, et al.
Pubblicazione: (2024)

Bayesian Predictive Coding
di: Tschantz, Alexander, et al.
Pubblicazione: (2025)

Advancing Multi-Organ Disease Care: A Hierarchical Multi-Agent Reinforcement Learning Framework
di: Tan, Daniel J., et al.
Pubblicazione: (2024)

MPRE: Multi-perspective Patient Representation Extractor for Disease Prediction
di: Yu, Ziyue, et al.
Pubblicazione: (2024)

Tackling Incomplete Data in Air Quality Prediction: A Bayesian Deep Learning Framework for Uncertainty Quantification
di: Pian, Yuzhuang, et al.
Pubblicazione: (2025)

Adaptive Graph Learning with Transformer for Multi-Reservoir Inflow Prediction
di: Hu, Pengfei, et al.
Pubblicazione: (2025)

How Transformers Learn to Plan via Multi-Token Prediction
di: Huang, Jianhao, et al.
Pubblicazione: (2026)

CE-SSL: Computation-Efficient Semi-Supervised Learning for ECG-based Cardiovascular Diseases Detection
di: Zhou, Rushuang, et al.
Pubblicazione: (2024)

Transformers can do Bayesian Clustering
di: Bhaskaran, Prajit, et al.
Pubblicazione: (2025)

Multi-task GINN-LP for Multi-target Symbolic Regression
di: Rajabu, Hussein, et al.
Pubblicazione: (2025)

Conformal Prediction as Bayesian Quadrature
di: Snell, Jake C., et al.
Pubblicazione: (2025)

A Comprehensive Machine Learning Framework for Heart Disease Prediction: Performance Evaluation and Future Perspectives
di: Lamir, Ali Azimi, et al.
Pubblicazione: (2025)

Survival Meets Classification: A Novel Framework for Early Risk Prediction Models of Chronic Diseases
di: Khan, Shaheer Ahmad, et al.
Pubblicazione: (2026)

A Swap-Adversarial Framework for Improving Domain Generalization in Electroencephalography-Based Parkinson's Disease Prediction
di: Jin, Seongwon, et al.
Pubblicazione: (2026)

Accident-Driven Congestion Prediction and Simulation: An Explainable Framework Using Advanced Clustering and Bayesian Networks
di: Talluri, Kranthi Kumar, et al.
Pubblicazione: (2025)

A Robust Framework for Secure Cardiovascular Risk Prediction: An Architectural Case Study of Differentially Private Federated Learning
di: Tertulino, Rodrigo, et al.
Pubblicazione: (2026)

ASDFormer: A Transformer with Mixtures of Pooling-Classifier Experts for Robust Autism Diagnosis and Biomarker Discovery
di: Izadi, Mohammad, et al.
Pubblicazione: (2025)

DiagnoLLM: A Hybrid Bayesian Neural Language Framework for Interpretable Disease Diagnosis
di: Xu, Bowen, et al.
Pubblicazione: (2025)

Bridging Data Gaps of Rare Conditions in ICU: A Multi-Disease Adaptation Approach for Clinical Prediction
di: Zhu, Mingcheng, et al.
Pubblicazione: (2025)

On Some Tunable Multi-fidelity Bayesian Optimization Frameworks
di: Manoj, Arjun, et al.
Pubblicazione: (2025)

Multi-Task Learning with Feature-Similarity Laplacian Graphs for Predicting Alzheimer's Disease Progression
di: Xu, Zixiang, et al.
Pubblicazione: (2025)

Efficient Multi-View Fusion and Flexible Adaptation to View Missing in Cardiovascular System Signals
di: Hu, Qihan, et al.
Pubblicazione: (2024)

Lifestyle-Informed Personalized Blood Biomarker Prediction via Novel Representation Learning
di: Heydari, A. Ali, et al.
Pubblicazione: (2024)

Bayesian Off-Policy Evaluation and Learning for Large Action Spaces
di: Aouali, Imad, et al.
Pubblicazione: (2024)

PhenoGnet: A Graph-Based Contrastive Learning Framework for Disease Similarity Prediction
di: Baminiwatte, Ranga, et al.
Pubblicazione: (2025)

FairMed-XGB: A Bayesian-Optimised Multi-Metric Framework with Explainability for Demographic Equity in Critical Healthcare Data
di: Goswami, Mitul, et al.
Pubblicazione: (2026)