Computational Biology in the Discovery of Biomarkers in the Diagnosis, Treatment and Management of Cardiovascular Diseases DOI

Irene Batta,

Ritika Patial,

Ranbir Chander Sobti

et al.

Cardiology and Cardiovascular Medicine, Journal Year: 2024, Volume and Issue: 8(5)

Published: Jan. 1, 2024

Cardiovascular diseases are the leading cause of mortality worldwide, with a disproportionately high burden in low- and middle-income countries. Biomarkers play crucial role early detection, diagnosis, treatment cardiovascular by providing valuable insights into normal abnormal conditions heart vascular system. The biomarkers derived from cells tissues can be identified quantified blood other body fluids tissues. Changes their expression level under pathological condition provide clinical information on underlying pathophysiology that could have predictive, diagnostic, prognostic value disease process, therefore incorporated guidelines. This enhances effectiveness risk stratification therapeutic decisions personalized medicine improvement patient outcomes. protein, carbohydrate, or genome-based may also lipids nucleic acids. Computational biology has emerged as powerful discipline biomarker discovery, leveraging computational techniques to identify validate biological markers for prognosis, drug response prediction. convergence advanced technologies, such artificial intelligence, multi-omics profiling, liquid biopsies, imaging, led significant shift discovery development biomarkers, enabling integration data multiple scales more comprehensive understanding complex signaling transcriptional networks pathogenesis. In this article, we reviewed integrated genomics, proteomics, metabolomics, together machine learning predictive modeling diseases. We discussed specific including epigenetic, metabolic, emerging extracellular vesicles, miRNAs, circular RNAs,

Language: Английский

ATEDU-NET: An Attention-Embedded Deep Unet for multi-disease diagnosis in chest X-ray images, breast ultrasound, and retina fundus DOI
Chukwuebuka Joseph Ejiyi, Zhen Qin, Victor Kwaku Agbesi

et al.

Computers in Biology and Medicine, Journal Year: 2025, Volume and Issue: 186, P. 109708 - 109708

Published: Jan. 21, 2025

Language: Английский

Citations

2
Advancing cancer diagnosis and prognostication through deep learning mastery in breast, colon, and lung histopathology with ResoMergeNet DOI
Chukwuebuka Joseph Ejiyi, Zhen Qin, Victor Kwaku Agbesi

et al.

Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 185, P. 109494 - 109494

Published: Dec. 4, 2024

Language: Английский

Citations

6
Attention-enriched deeper UNet (ADU-NET) for disease diagnosis in breast ultrasound and retina fundus images DOI
Chukwuebuka Joseph Ejiyi, Zhen Qin, Victor Kwaku Agbesi

et al.

Progress in Artificial Intelligence, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 3, 2024

Language: Английский

Citations

4
Polynomial-SHAP analysis of liver disease markers for capturing of complex feature interactions in machine learning models DOI
Chukwuebuka Joseph Ejiyi, Dongsheng Cai,

Makuachukwu Bennedith Ejiyi

et al.

Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 182, P. 109168 - 109168

Published: Sept. 28, 2024

Language: Английский

Citations

4
Ms-Cfa:Multi-Scale Coarse-to-Fine Attention is Used To Segment in Medical Ultrasound Images DOI
Hao Yang, Lingfeng Wang, Wei Li

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
Breast cancer prediction with feature-selected XGB classifier, optimized by metaheuristic algorithms DOI Creative Commons
Palash Sarker, Amel Ksibi, Mona Jamjoom

et al.

Journal Of Big Data, Journal Year: 2025, Volume and Issue: 12(1)

Published: April 1, 2025

Language: Английский

Citations

0
Polynomial-SHAP as a SMOTE alternative in conglomerate neural networks for realistic data augmentation in cardiovascular and breast cancer diagnosis DOI Creative Commons
Chukwuebuka Joseph Ejiyi, Dongsheng Cai,

Francis Ofoma Eze

et al.

Journal Of Big Data, Journal Year: 2025, Volume and Issue: 12(1)

Published: April 18, 2025

Language: Английский

Citations

0
Improved deep neural network (EnhanceNet) for real-time detection of some publicly prohibited items DOI
Chukwuebuka Joseph Ejiyi, Zhen Qin, Chiagoziem C. Ukwuoma

et al.

Network Computation in Neural Systems, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 28

Published: Sept. 11, 2024

Public safety is a critical concern, typically addressed through security checks at entrances of public places, involving trained officers or X-ray scanning machines to detect prohibited items. However, many places like hospitals, schools, and event centres lack such resources, risking breaches. Even with scanners manual checks, gaps can be exploited by individuals malicious intent, posing significant risks. Additionally, traditional methods, relying on inspections conventional image processing techniques, are often inefficient prone high error rates. To mitigate these risks, we propose real-time detection model - EnhanceNet using customized Scale-Enhanced Pooling Network (SEP-Net) integrated into the YOLOv4. The innovative SEP-Net enhances feature representation localization accuracy, significantly contributing model's efficacy in detecting We annotated custom dataset nine classes evaluated our models different input sizes (608 416). 608 size achieved mean Average Precision (mAP) 74.10% speed 22.3 Frames per Second (FPS). 416 showed superior performance, achieving mAP 76.75% 27.1 FPS. These demonstrate that accurate efficient, making them suitable for applications.

Language: Английский

Citations

1
Computational Biology in the Discovery of Biomarkers in the Diagnosis, Treatment and Management of Cardiovascular Diseases DOI

Irene Batta,

Ritika Patial,

Ranbir Chander Sobti

et al.

Cardiology and Cardiovascular Medicine, Journal Year: 2024, Volume and Issue: 8(5)

Published: Jan. 1, 2024

Cardiovascular diseases are the leading cause of mortality worldwide, with a disproportionately high burden in low- and middle-income countries. Biomarkers play crucial role early detection, diagnosis, treatment cardiovascular by providing valuable insights into normal abnormal conditions heart vascular system. The biomarkers derived from cells tissues can be identified quantified blood other body fluids tissues. Changes their expression level under pathological condition provide clinical information on underlying pathophysiology that could have predictive, diagnostic, prognostic value disease process, therefore incorporated guidelines. This enhances effectiveness risk stratification therapeutic decisions personalized medicine improvement patient outcomes. protein, carbohydrate, or genome-based may also lipids nucleic acids. Computational biology has emerged as powerful discipline biomarker discovery, leveraging computational techniques to identify validate biological markers for prognosis, drug response prediction. convergence advanced technologies, such artificial intelligence, multi-omics profiling, liquid biopsies, imaging, led significant shift discovery development biomarkers, enabling integration data multiple scales more comprehensive understanding complex signaling transcriptional networks pathogenesis. In this article, we reviewed integrated genomics, proteomics, metabolomics, together machine learning predictive modeling diseases. We discussed specific including epigenetic, metabolic, emerging extracellular vesicles, miRNAs, circular RNAs,

Language: Английский

Citations

1