High-dimensional -omics data such as genomic, transcriptomic, and metabolomic data offer great promise in advancing precision medicine. In particular, such data have enabled the investigation of ...

Statistical machine learning is at the core of modern-day advances in artificial intelligence, but a Rochester Institute of Technology professor argues that applying it correctly requires equal parts ...

A prior course in statistics at the level of IEMS 304; A course in matrix analysis; Proficiency in programming as coding will be a significant part of the class. This course examines a modern ...

Statistical modeling continues to deliver distinct value to businesses both independent of, and in concert with, machine learning. “Artificial intelligence” (AI) and “machine learning” are among the ...

The Statistical & Data Sciences (SDS) Program links faculty and students from across the college interested in learning things from data. At Smith, students learn statistics by doing—class time ...

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...

The Annals of Statistics, Vol. 42, No. 6 (December 2014), pp. 2164-2201 (38 pages) We provide theoretical analysis of the statistical and computational properties of penalized M-estimators that can be ...

Selection of appropriate adjuvant therapy to ultimately reduce the risk of breast cancer (BC) recurrence is a challenge for medical oncologists. Several automated risk prediction models have been ...