WCN25-4420 PREDICTING DRY WEIGHT IN HEMODIALYSIS PATIENTS USING DEEP LEARNING TECHNIQUES
interest were South Dakota (100), Alabama (100), Tennessee (100), Mississippi (97), and West Virginia (92).In contrast, lowest interest was observed in New Jersey (57), Oregon (57), Utah (56), Colorado (53), and District of Columbia (43) (Figure 1C).Conclusions: This study highlights significantly steady increase in public interest in chronic kidney disease, both globally and within the United States.These findings also indicate regional health disparities, higher disease prevalence, lack of healthcare access, and lower digital knowledge.Even though, understanding these trends is crucial for identifying areas where public awareness is lacking, which in turn can help to tailor and target preventive and treatment strategies more effectively.Public health campaigns should focus on these key areas, utilizing digital platforms and ensuring accessible, readable information for all populations.I have no potential conflict of interest to disclose.I did not use generative AI and AI-assisted technologies in the writing process.
Authors
- Anand Chellappan (ORCID: https://orcid.org/0000-0003-3265-3586)
- Poonam Sharma (ORCID: https://orcid.org/0000-0003-0766-5171)
- Abhishek Singh (ORCID: https://orcid.org/0009-0006-7537-8173)
- Abhinav Konkal
Institutions
- Visvesvaraya National Institute of Technology (IN)
- Government Medical College (IN)
- Nagpur Institute of Technology (IN)
- Central India Institute of Medical Sciences (IN)
- All India Institute of Medical Sciences, Nagpur (IN)
Publication Details
- Journal
- Kidney International Reports
- Published
- 2025-01-27
- DOI
- https://doi.org/10.1016/j.ekir.2024.11.188
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00