AIMC Topic: Quality Improvement

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Dosimetric study on learning-based cone-beam CT correction in adaptive radiation therapy.

Medical dosimetry : official journal of the American Association of Medical Dosimetrists
INTRODUCTION: Cone-beam CT (CBCT) image quality is important for its quantitative analysis in adaptive radiation therapy. However, due to severe artifacts, the CBCTs are primarily used for verifying patient setup only so far. We have developed a lear...

Machine learning concepts, concerns and opportunities for a pediatric radiologist.

Pediatric radiology
Machine learning, a subfield of artificial intelligence, is a rapidly evolving technology that offers great potential for expanding the quality and value of pediatric radiology. We describe specific types of learning, including supervised, unsupervis...

Artificial intelligence and colonoscopy: Current status and future perspectives.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
BACKGROUND AND AIM: Application of artificial intelligence in medicine is now attracting substantial attention. In the field of gastrointestinal endoscopy, computer-aided diagnosis (CAD) for colonoscopy is the most investigated area, although it is s...

Using Machine Learning to Identify Change in Surgical Decision Making in Current Use of Damage Control Laparotomy.

Journal of the American College of Surgeons
BACKGROUND: In an earlier study, we reported the successful reduction in the use of damage control laparotomy (DCL); however, no change in the relative frequencies of specific indications was observed. In this study, we aimed to use machine learning ...

Novel knowledge-based system with relation detection and textual evidence for question answering research.

PloS one
With the development of large-scale knowledge bases (KBs), knowledge-based question answering (KBQA) has become an important research topic in recent years. The key task in KBQA is relation detection, which is the process of finding a compatible answ...

Autonomous detection, grading, and reporting of postoperative complications using natural language processing.

Surgery
INTRODUCTION: Natural language processing, a computer science technique that allows interpretation of narrative text, is infrequently used to identify surgical complications. We designed a natural language processing algorithm to identify and grade t...

Artificial Intelligence and Radiology: A Social Media Perspective.

Current problems in diagnostic radiology
OBJECTIVE: To use Twitter to characterize public perspectives regarding artificial intelligence (AI) and radiology.

Towards improving diagnosis of skin diseases by combining deep neural network and human knowledge.

BMC medical informatics and decision making
BACKGROUND: The emergence of the deep convolutional neural network (CNN) greatly improves the quality of computer-aided supporting systems. However, due to the challenges of generating reliable and timely results, clinical adoption of computer-aided ...