Balaji Veeraraghavan
Biographic Data
| ID | 7019762 |
|---|---|
| NAME | Balaji Veeraraghavan |
| GIVEN NAMES | Balaji |
| FAMILY NAME | Veeraraghavan |
| SIGNATURE | VEERARAGHAVAN B |
| AFFILIATIONS | christian medical college, vellore |
| ORCID | 0000-0002-8662-4257 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Uncloaking the black-box
Antimicrobial resistance and emerging infectious diseases remain significant challenges for global health, driving a need for advanced technological solutions. Artificial Intelligence (AI) expanded opportunities in clinical microbiology, infectious diseases, and public health by harnessing vast, structured datasets. Despite impressive analytical capabilities, the clinical integration of AI-based applications is hindered by its opacity. The “black…
A strategic approach to regulating new antimicrobials
Antimicrobial resistance (AMR) is a significant threat to healthcare in India, which is experiencing increasing resistance to critical antibiotics, including last-resort treatments. Emerging data indicate that resistance to last resort life-saving drugs continues to rise, limiting treatment options for drug-resistant infections. While the introduction of new antimicrobials offers hope, historical patterns suggest that resistance may develop rapid…
Assessing Seasonality Variation with Harmonic Regression
The use of the harmonic regression model is well accepted in the epidemiological and biostatistical communities as a standard procedure to examine seasonal patterns in disease occurrence. While these models may provide good fit to periodic patterns with relatively symmetric rises and falls, for some diseases the incidence fluctuates in a more complex manner. We propose a two-step harmonic regression approach to improve the model fit for data exhi…
Spatiotemporal Patterns of Cholera Hospitalization in Vellore, India
Systematically collected hospitalization records provide valuable insight into disease patterns and support comprehensive national infectious disease surveillance networks. Hospitalization records detailing patient's place of residence (PoR) can be utilized to better understand a hospital's case load and strengthen surveillance among mobile populations. This study examined geographic patterns of patients treated for cholera at a major hospital in…
No prominent works on this page.
Spatiotemporal Patterns of Cholera Hospitalization in Vellore, India
Systematically collected hospitalization records provide valuable insight into disease patterns and support comprehensive national infectious disease surveillance networks. Hospitalization records detailing patient's place of residence (PoR) can be utilized to better understand a hospital's case load and strengthen surveillance among mobile populations. This study examined geographic patterns of patients treated for cholera at a major hospital in…
Assessing Seasonality Variation with Harmonic Regression
The use of the harmonic regression model is well accepted in the epidemiological and biostatistical communities as a standard procedure to examine seasonal patterns in disease occurrence. While these models may provide good fit to periodic patterns with relatively symmetric rises and falls, for some diseases the incidence fluctuates in a more complex manner. We propose a two-step harmonic regression approach to improve the model fit for data exhi…
A strategic approach to regulating new antimicrobials
Antimicrobial resistance (AMR) is a significant threat to healthcare in India, which is experiencing increasing resistance to critical antibiotics, including last-resort treatments. Emerging data indicate that resistance to last resort life-saving drugs continues to rise, limiting treatment options for drug-resistant infections. While the introduction of new antimicrobials offers hope, historical patterns suggest that resistance may develop rapid…
Uncloaking the black-box
Antimicrobial resistance and emerging infectious diseases remain significant challenges for global health, driving a need for advanced technological solutions. Artificial Intelligence (AI) expanded opportunities in clinical microbiology, infectious diseases, and public health by harnessing vast, structured datasets. Despite impressive analytical capabilities, the clinical integration of AI-based applications is hindered by its opacity. The “black…
COVID-19 epidemiological studies (2 works) · Medicine (2 works) · Animal Disease Management and Epidemiology (1 works) · Antibiotic resistance (1 works) · Antibiotic Use and Resistance (1 works) · Antimicrobial (1 works) · Artificial Intelligence in Healthcare and Education (1 works) · Bacterial Identification and Susceptibility Testing (1 works) · BENGAL (1 works) · Biology (1 works)