Alanay, A. 2020. Use of Predictive Machine Learning Models at the Population Level Has the Potential to Save Cost by Directing Economic Resources to Those Likely to Improve Most: A Simulation Analysis Stratified by Risk in Largest Combined US/European ASD Registry. SRS Annual Meeting , 38.

Alanay, A., (2020). Use of Predictive Machine Learning Models at the Population Level Has the Potential to Save Cost by Directing Economic Resources to Those Likely to Improve Most: A Simulation Analysis Stratified by Risk in Largest Combined US/European ASD Registry . SRS Annual Meeting (pp.38).

Alanay, Ahmet. "Use of Predictive Machine Learning Models at the Population Level Has the Potential to Save Cost by Directing Economic Resources to Those Likely to Improve Most: A Simulation Analysis Stratified by Risk in Largest Combined US/European ASD Registry," SRS Annual Meeting, 2020

Alanay, Ahmet. "Use of Predictive Machine Learning Models at the Population Level Has the Potential to Save Cost by Directing Economic Resources to Those Likely to Improve Most: A Simulation Analysis Stratified by Risk in Largest Combined US/European ASD Registry." SRS Annual Meeting , pp.38, 2020

Alanay, A. (2020) . "Use of Predictive Machine Learning Models at the Population Level Has the Potential to Save Cost by Directing Economic Resources to Those Likely to Improve Most: A Simulation Analysis Stratified by Risk in Largest Combined US/European ASD Registry." SRS Annual Meeting , p.38.

@conferencepaper{conferencepaper, author={Ahmet ALANAY}, title={Use of Predictive Machine Learning Models at the Population Level Has the Potential to Save Cost by Directing Economic Resources to Those Likely to Improve Most: A Simulation Analysis Stratified by Risk in Largest Combined US/European ASD Registry}, congress name={SRS Annual Meeting}, city={}, country={}, year={2020}, pages={38} }