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 ...
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 ...
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 ...
This course provides foundational and advanced concepts in statistical learning theory, essential for analyzing complex data and making informed predictions. Students will delve into both asymptotic ...
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 ...
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 ...
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 ...
The groundwork for machine learning was laid down in the middle of last century. But increasingly powerful computers – harnessed to algorithms refined over the past decade – are driving an explosion ...
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