Using machine learning to create a system for predicting blood pressure decline from thermographic images during anesthesia induction

Using machine learning to create a system for predicting blood pressure decline from thermographic images during anesthesia induction - Using machine learning to create a system for predicting blood pressure decline from thermographic images during anesthesia induction

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000044725

Enrollment

500

Registered

2021-07-02

Start date

2021-07-05

Completion date

Unknown

Last updated

2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Elective surgery patients

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: Patients undergoing elective surgery at Yamagata University Hospital

Exclusion criteria

Exclusion criteria: Cardiac surgery Patients with predicted peripheral circulatory blood flow disturbances

Design outcomes

Primary

Measure	Time frame
Create a classifier (system) that can discriminate between drops in blood pressure, create a receiver operating characteristic curve, and determine sensitivity and specificity.	—

Countries

Japan

Contacts

Public ContactMisato Kurota

Yamagata University Faculty of Medicine Department of Anesthesiology

patsykurota224@gmail.com023-628-5400

Outcome results