Use of AI in Diagnostic Imaging and Future Prospects

抄録

Introduction: The integration of artificial intelligence (AI) into medical practices has transformed fields like gastroenterological surgery. AI predicts patient prognoses using clinical and pathological data and develops technologies that create three-dimensional (3D) models for surgical simulations, thereby enhancing surgical precision and care quality.

Methods: At our facility, AI-driven diagnostic and treatment systems have been developed under the "Strategic Innovation Creation Program" by the Cabinet Office. Our research focuses on perioperative care by constructing 3D models from preoperative imaging data to develop surgical support systems for preoperative simulations and navigation during surgery. Additionally, we use deep learning to predict disease progression and complications and natural language processing to analyze electronic medical records to predict postoperative complications.

Results: AI-based surgical support systems effectively convert two-dimensional imaging data into 3D models, thereby improving surgical precision. Predictive models for disease progression and complications developed using deep learning have high accuracy. AI applications in diagnostic imaging enable early detection and improved treatment planning. AI-based tools for informed consent and patient support enhance patient understanding and satisfaction.

Conclusions: AI revolutionizes medical practices by improving diagnostic accuracy, surgical precision, and patient outcomes. Future projects will integrate remote diagnostic and treatment planning; leverage AI for comprehensive, high-quality care; and support work-style reforms for healthcare professionals. Advancements in AI will overcome current medical challenges and enhance the communication between physicians and patients.