Plattform for Operation Scheduling and Prediction using Machine learning

Plattform for Operation Scheduling and Prediction using Machine learning - PROSPER

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00025077

Enrollment

36000

Registered

2021-04-16

Start date

2021-04-18

Completion date

Unknown

Last updated

2025-04-07

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

Conditions

No focus on a specific disease

Interventions

Group 1: For the prediction of surgery time based on patient- and surgery-dependent variables, data sets of all surgeries at the Clinic and Polyclinic for Visceral, Thoracic and Vascular Surgery at th

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: none

Exclusion criteria

Exclusion criteria: none

Design outcomes

Primary

Measure	Time frame
prognosis of operation duration	—

Secondary

Measure	Time frame
Optimal utilisation of resources in the operating rooms up-to-the-minute planning Integration of emergencies into the OR planning	—

Countries

Germany

Contacts

Public ContactGrit Krause-Jüttler

Universitätsklinikum Dresden Klinik für Viszeral-, Thorax- und Gefäßchirurgie

grit.krause-juettler@ukdd.de0351-45819410

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 12, 2026