AIMC Topic: Quality Assurance, Health Care

Clear Filters Showing 31 to 40 of 91 articles

A Novel Use of Artificial Intelligence to Examine Diversity and Hospital Performance.

The Journal of surgical research
BACKGROUND: The US population is becoming more racially and ethnically diverse. Research suggests that cultural diversity within organizations can increase team potency and performance, yet this theory has not been explored in the field of surgery. F...

Error detection using a convolutional neural network with dose difference maps in patient-specific quality assurance for volumetric modulated arc therapy.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
The aim of this study was to evaluate the use of dose difference maps with a convolutional neural network (CNN) to detect multi-leaf collimator (MLC) positional errors in patient-specific quality assurance for volumetric modulated radiation therapy (...

The Impact of Artificial Intelligence and Machine Learning in Radiation Therapy: Considerations for Future Curriculum Enhancement.

Journal of medical imaging and radiation sciences
Artificial intelligence (AI) and machine learning (ML) approaches have caught the attention of many in health care. Current literature suggests there are many potential benefits that could transform future clinical workflows and decision making. Embe...

Automatic classification of dental artifact status for efficient image veracity checks: effects of image resolution and convolutional neural network depth.

Physics in medicine and biology
Enabling automated pipelines, image analysis and big data methodology in cancer clinics requires thorough understanding of the data. Automated quality assurance steps could improve the efficiency and robustness of these methods by verifying possible ...

CAD and AI for breast cancer-recent development and challenges.

The British journal of radiology
Computer-aided diagnosis (CAD) has been a popular area of research and development in the past few decades. In CAD, machine learning methods and multidisciplinary knowledge and techniques are used to analyze the patient information and the results ca...

Artificial Intelligence in Radiation Oncology.

Hematology/oncology clinics of North America
The integration of artificial intelligence in the radiation oncologist's workflow has multiple applications and significant potential. From the initial patient encounter, artificial intelligence may aid in pretreatment disease outcome and toxicity pr...

Quality assurance of computer-aided detection and diagnosis in colonoscopy.

Gastrointestinal endoscopy
Recent breakthroughs in artificial intelligence (AI), specifically via its emerging sub-field "deep learning," have direct implications for computer-aided detection and diagnosis (CADe and/or CADx) for colonoscopy. AI is expected to have at least 2 m...

Radiation Therapy Quality Assurance Tasks and Tools: The Many Roles of Machine Learning.

Medical physics
The recent explosion in machine learning efforts in the quality assurance (QA) space has produced a variety of proofs-of-concept many with promising results. Expected outcomes of model implementation include improvements in planning time, plan qualit...

Machine learning for automated quality assurance in radiotherapy: A proof of principle using EPID data description.

Medical physics
PURPOSE: Developing automated methods to identify task-driven quality assurance (QA) procedures is key toward increasing safety, efficacy, and efficiency. We investigate the use of machine learning (ML) methods for possible visualization, automation,...