Applications of Artificial Intelligence in Acute Abdominal Imaging

Area of Science:

• Radiology
• Medical Imaging
• Artificial Intelligence

Background:

• Acute abdominal pain is a frequent clinical presentation requiring prompt diagnosis.
• Emergent abdominal imaging is crucial for identifying life-threatening conditions.
• Artificial intelligence (AI) offers potential advancements in interpreting these urgent scans.

Purpose of the Study:

• To review the evolution and trends of AI applications in evaluating acute abdominal pathologies.
• To explore AI's role in both traumatic and non-traumatic abdominal imaging.
• To discuss the clinical impact, challenges, and future directions of AI in this field.

Main Methods:

• Narrative review of existing literature on AI in acute abdominal imaging.
• Analysis of AI model performance across different imaging modalities (CT, radiographs, ultrasound).
• Examination of AI applications for specific pathologies like appendicitis, bowel obstruction, and cholecystitis.

Main Results:

• Numerous studies demonstrate AI's capability in detecting common abdominal pathologies.
• AI models range from basic classification to advanced severity assessment.
• AI applications are being developed for both traumatic and non-traumatic acute abdominal conditions.

Conclusions:

• AI is a rapidly advancing field with significant implications for acute abdominal pain diagnosis.
• AI has the potential to enhance clinical decision-making and improve patient outcomes in emergent imaging.
• Further research and development are needed to overcome challenges and fully realize AI's clinical impact.