CliniLiver: Leveraging Clinical Data for Liver Disease Prognosis
In an era defined by rapid change, the importance of precise medical prognoses cannot be overstated, and CliniLiver stands at the forefront of this critical endeavour. Leveraging clinical data, our innovative approach aims to predict the outcome of liver disease with unparalleled accuracy. By meticulously analysing patient baseline characteristics and metastases profiles, we've developed a sophisticated machine learning model capable of forecasting the occurrence of the of liver disease. Moreover, it aligns with broader efforts in predictive modelling using electronic health records, where studies have achieved impressive accuracy rates of 70-72% in anticipating individualized treatment responses for liver disease. CliniLiver represents a transformative leap forward in medical prognosis, offering the potential to revolutionize liver disease management through informed decisions with the presence of the liver disease.
Authors
- D. Kavitha
- Gireesh Babu C N
- Girisha Balaraju (ORCID: https://orcid.org/0000-0002-3688-2864)
- Chandrashekhara K T (ORCID: https://orcid.org/0000-0001-5973-2132)
- Abhishek Reddy (ORCID: https://orcid.org/0000-0003-4035-1465)
- B Indhuja
Institutions
- REVA University (IN)
Publication Details
- Published
- 2024-11-23
- DOI
- https://doi.org/10.1109/icec59683.2024.10837279
- Citations
- 5
- Primary Topic
- Liver Disease Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.93