Aviroop Biswas
Biographic Data
| ID | 3926941 |
|---|---|
| NAME | Aviroop Biswas |
| GIVEN NAMES | Aviroop |
| FAMILY NAME | Biswas |
| SIGNATURE | BISWAS A |
| AFFILIATIONS | From the Institute of Health Policy, Management and Evaluation, and the Faculty of Kinesiology and Physical Education, University of Toronto; University Health Network–Toronto Rehabilitation Institute, Cardiovascular Prevention and Rehabilitation Program; Sunnybrook Health Sciences Centre; York University; and Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada. |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2015 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Machine learning and the labor market
ML exposure is segmented according to occupational and worker sociodemographic characteristics and has the potential to widen inequities in the working population. ML may have a gendered effect and disproportionately impact certain groups of women when compared to men. We provide a critical evidence base to inform strategic responses that ensure inclusion in a working world where ML is commonplace
Sedentary Time and Its Association With Risk for Disease Incidence, Mortality, and Hospitalization in Adults
BACKGROUND: The magnitude, consistency, and manner of association between sedentary time and outcomes independent of physical activity remain unclear. PURPOSE: To quantify the association between sedentary time and hospitalizations, all-cause mortality, cardiovascular disease, diabetes, and cancer in adults independent of physical activity. DATA SOURCES: English-language studies in MEDLINE, PubMed, EMBASE, CINAHL, Cochrane Library, Web of Knowled…
No prominent works on this page.
Sedentary Time and Its Association With Risk for Disease Incidence, Mortality, and Hospitalization in Adults
BACKGROUND: The magnitude, consistency, and manner of association between sedentary time and outcomes independent of physical activity remain unclear. PURPOSE: To quantify the association between sedentary time and hospitalizations, all-cause mortality, cardiovascular disease, diabetes, and cancer in adults independent of physical activity. DATA SOURCES: English-language studies in MEDLINE, PubMed, EMBASE, CINAHL, Cochrane Library, Web of Knowled…
Machine learning and the labor market
ML exposure is segmented according to occupational and worker sociodemographic characteristics and has the potential to widen inequities in the working population. ML may have a gendered effect and disproportionately impact certain groups of women when compared to men. We provide a critical evidence base to inform strategic responses that ensure inclusion in a working world where ML is commonplace
Medicine (2 works) · Bachelor (1 works) · Cardiovascular and exercise physiology (1 works) · CINAHL (1 works) · Cochrane Library (1 works) · Cohort study (1 works) · Confidence interval (1 works) · Demographic economics (1 works) · Demography (1 works) · Demography (1 works)