Researchers developed a machine learning model that uses MRI data to predict severe complications in placenta accreta spectrum (PAS) cases.
Key Details
- 1Placenta accreta spectrum is a serious perinatal complication linked to maternal mortality.
- 2Cases of PAS have risen in part due to increased cesarean deliveries.
- 3Machine learning techniques are being applied to MRI data to predict risk of severe outcomes before delivery.
- 4Accurate pre-delivery risk prediction may improve clinical management and outcomes for PAS patients.
Why It Matters
Integrating machine learning with MRI could offer earlier, more accurate risk stratification for PAS, helping radiologists and clinicians manage high-risk obstetric patients and potentially reduce maternal morbidity and mortality.
Source
Health Imaging
Related News
•Radiology Business
Google's Gemini Outperforms Providers in Communicating IR Procedures
Large language models like Google's Gemini demonstrate higher accuracy and greater empathy than human providers when answering patient questions about interventional radiology.
•AuntMinnie
Comparing False-Positive Findings: AI vs. Radiologists in DBT Screening
AI and radiologists differ in the types and patient characteristics of false-positive findings in digital breast tomosynthesis breast cancer screening.
•Radiology Business
AI Triage Cuts CT Report Turnaround for Pulmonary Embolism—Daytime Only
FDA-backed study finds AI triage tools reduce radiology CT report turnaround times for pulmonary embolism during peak hours.