Qureshi, Nadeem

Can machine-learning improve cardiovascular risk prediction using routine clinical data?

Weng, S. F., Reps, J., Kai, J., Garibaldi, J. M., & Qureshi, N. (2017) · PLOS ONE

Artificial Intelligence in HealthcareMachine Learning in Healthcare

Cited by 1,346

Achieving change in primary care—causes of the evidence to practice gap: systematic reviews of reviews

Lau, R., Stevenson, F., Ong, B. N., Dziedzic, K., Treweek, S., Eldridge, S., Everitt, H., Kennedy, A., Qureshi, N., Rogers, A., et al. (2015) · Implementation Science

Health Policy Implementation ScienceHealth Sciences Research and Education

Cited by 533

Achieving change in primary care—effectiveness of strategies for improving implementation of complex interventions: systematic review of reviews

Lau, R., Stevenson, F., Ong, B. N., Dziedzic, K., Treweek, S., Eldridge, S., Everitt, H., Kennedy, A., Qureshi, N., Rogers, A., et al. (2015) · BMJ Open

Health Policy Implementation ScienceClinical practice guidelines implementation

Cited by 254

Prediction of premature all-cause mortality: A prospective general population cohort study comparing machine-learning and standard epidemiological approaches

Weng, S. F., Vaz, L., Qureshi, N., & Kai, J. (2019) · PLOS ONE

Artificial Intelligence in HealthcareMachine Learning in Healthcare

Cited by 118

Addressing the evidence to practice gap for complex interventions in primary care: a systematic review of reviews protocol

Lau, R., Stevenson, F., Ong, B. N., Dziedzic, K., Eldridge, S., Everitt, H., Kennedy, A., Kontopantelis, E., Little, P., Qureshi, N., et al. (2014) · BMJ Open

Health Policy Implementation ScienceHealth Sciences Research and Education

Cited by 26