Linking Preoperative and Intraoperative Data for Risk Prediction: More Answers or Just More Data?

Seshadri C Mudumbai^{1

2

3}, Parisa Rashidi^{4

5}

Affiliations

¹ Anesthesiology and Perioperative Care Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, California.
² Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California.
³ Center for Innovation to Implementation, Veterans Affairs Palo Alto Health Care System, Menlo Park, California.
⁴ Biomedical Engineering, University of Florida, Gainesville.
⁵ Electrical and Computer Engineering, University of Florida, Gainesville.

Free article

Comment

Seshadri C Mudumbai et al. JAMA Netw Open. 2021.

Free article

. 2021 Mar 1;4(3):e212547.

doi: 10.1001/jamanetworkopen.2021.2547.

Seshadri C Mudumbai^{1

2

3}, Parisa Rashidi^{4

5}

¹ Anesthesiology and Perioperative Care Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, California.
² Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California.
³ Center for Innovation to Implementation, Veterans Affairs Palo Alto Health Care System, Menlo Park, California.
⁴ Biomedical Engineering, University of Florida, Gainesville.
⁵ Electrical and Computer Engineering, University of Florida, Gainesville.

No abstract available

Comment on

Use of Machine Learning to Develop and Evaluate Models Using Preoperative and Intraoperative Data to Identify Risks of Postoperative Complications.
Xue B, Li D, Lu C, King CR, Wildes T, Avidan MS, Kannampallil T, Abraham J. Xue B, et al. JAMA Netw Open. 2021 Mar 1;4(3):e212240. doi: 10.1001/jamanetworkopen.2021.2240. JAMA Netw Open. 2021. PMID: 33783520 Free PMC article.