Exploring Emerging and Innovative Biomarkers for the Assessment and Monitoring of Cardiovascular Disease Risk and Treatment Efficacy in Patients
The current research examines the creation of biomarkers for measuring cardiovascular disease (CVD) risk and tracking therapy effectiveness. While current biomarkers like cholesterol levels and troponins are useful, developing and innovating new biomarkers gives fresh insights into CVD etiology and...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wolters Kluwer Medknow Publications
2025-03-01
|
| Series: | APIK Journal of Internal Medicine |
| Subjects: | |
| Online Access: | https://journals.lww.com/10.4103/ajim.ajim_45_24 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849769031895089152 |
|---|---|
| author | Omar Elsaka |
| author_facet | Omar Elsaka |
| author_sort | Omar Elsaka |
| collection | DOAJ |
| description | The current research examines the creation of biomarkers for measuring cardiovascular disease (CVD) risk and tracking therapy effectiveness. While current biomarkers like cholesterol levels and troponins are useful, developing and innovating new biomarkers gives fresh insights into CVD etiology and drug response. The limits of known biomarkers are discussed, leading to the quest for new signs that might enhance risk categorization and therapy monitoring. Advancements in multiomics technologies, such as genomics, proteomics, metabolomics, and transcriptomics, have been utilized to uncover possible biomarkers, offering a complete perspective of molecular pathways implicated in CVD. Artificial intelligence and machine learning play a vital role in biomarker development and validation, allowing the investigation of massive omics datasets and detecting patterns and links that may not be obvious using conventional approaches. The clinical translation of new biomarkers needs comprehensive validation and evaluation of their efficacy in improving patient outcomes. Incorporating these indicators into clinical practice might boost risk prediction, modify treatment regimens, and improve overall CVD care. |
| format | Article |
| id | doaj-art-aeb0152f4eed45d2a980fa8114b88d99 |
| institution | DOAJ |
| issn | 2666-1802 2666-1810 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Wolters Kluwer Medknow Publications |
| record_format | Article |
| series | APIK Journal of Internal Medicine |
| spelling | doaj-art-aeb0152f4eed45d2a980fa8114b88d992025-08-20T03:03:36ZengWolters Kluwer Medknow PublicationsAPIK Journal of Internal Medicine2666-18022666-18102025-03-011329410110.4103/ajim.ajim_45_24Exploring Emerging and Innovative Biomarkers for the Assessment and Monitoring of Cardiovascular Disease Risk and Treatment Efficacy in PatientsOmar ElsakaThe current research examines the creation of biomarkers for measuring cardiovascular disease (CVD) risk and tracking therapy effectiveness. While current biomarkers like cholesterol levels and troponins are useful, developing and innovating new biomarkers gives fresh insights into CVD etiology and drug response. The limits of known biomarkers are discussed, leading to the quest for new signs that might enhance risk categorization and therapy monitoring. Advancements in multiomics technologies, such as genomics, proteomics, metabolomics, and transcriptomics, have been utilized to uncover possible biomarkers, offering a complete perspective of molecular pathways implicated in CVD. Artificial intelligence and machine learning play a vital role in biomarker development and validation, allowing the investigation of massive omics datasets and detecting patterns and links that may not be obvious using conventional approaches. The clinical translation of new biomarkers needs comprehensive validation and evaluation of their efficacy in improving patient outcomes. Incorporating these indicators into clinical practice might boost risk prediction, modify treatment regimens, and improve overall CVD care.https://journals.lww.com/10.4103/ajim.ajim_45_24artificial intelligencebiomarkerscardiovascular diseaseemerginginnovativemonitoringmultiomicsprecision medicinerisk assessmenttreatment efficacy |
| spellingShingle | Omar Elsaka Exploring Emerging and Innovative Biomarkers for the Assessment and Monitoring of Cardiovascular Disease Risk and Treatment Efficacy in Patients APIK Journal of Internal Medicine artificial intelligence biomarkers cardiovascular disease emerging innovative monitoring multiomics precision medicine risk assessment treatment efficacy |
| title | Exploring Emerging and Innovative Biomarkers for the Assessment and Monitoring of Cardiovascular Disease Risk and Treatment Efficacy in Patients |
| title_full | Exploring Emerging and Innovative Biomarkers for the Assessment and Monitoring of Cardiovascular Disease Risk and Treatment Efficacy in Patients |
| title_fullStr | Exploring Emerging and Innovative Biomarkers for the Assessment and Monitoring of Cardiovascular Disease Risk and Treatment Efficacy in Patients |
| title_full_unstemmed | Exploring Emerging and Innovative Biomarkers for the Assessment and Monitoring of Cardiovascular Disease Risk and Treatment Efficacy in Patients |
| title_short | Exploring Emerging and Innovative Biomarkers for the Assessment and Monitoring of Cardiovascular Disease Risk and Treatment Efficacy in Patients |
| title_sort | exploring emerging and innovative biomarkers for the assessment and monitoring of cardiovascular disease risk and treatment efficacy in patients |
| topic | artificial intelligence biomarkers cardiovascular disease emerging innovative monitoring multiomics precision medicine risk assessment treatment efficacy |
| url | https://journals.lww.com/10.4103/ajim.ajim_45_24 |
| work_keys_str_mv | AT omarelsaka exploringemergingandinnovativebiomarkersfortheassessmentandmonitoringofcardiovasculardiseaseriskandtreatmentefficacyinpatients |