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Medical Audit

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A Novel Natural Language Processing Tool Improves Colonoscopy Auditing of Adenoma and Serrated Polyp Detection Rates.

Journal of gastroenterology and hepatology
BACKGROUND AND STUDY AIMS: Determining adenoma detection rate (ADR) and serrated polyp detection rate (SDR) can be challenging as they usually involve manual matching of colonoscopy and histology reports. This study aimed to validate a Natural Langua...

Effectiveness and clinical impact of using deep learning for first-trimester fetal ultrasound image quality auditing.

BMC pregnancy and childbirth
BACKGROUND: Regular auditing of ultrasound images is required to maintain quality; however, manual auditing is time-consuming and can be inconsistent. We therefore aimed to develop and validate an artificial intelligence-based image quality audit (AI...

Can natural language processing be effectively applied for audit data analysis in gynaecological oncology at a UK cancer centre?

International journal of medical informatics
BACKGROUND: The British Gynaecological Cancer Society (BGCS) has highlighted the disparity of ovarian cancer outcomes in the UK compared to other European countries. Therefore, cancer quality assurance audits and subspecialty training are important i...

Applying Machine Learning Across Sites: External Validation of a Surgical Site Infection Detection Algorithm.

Journal of the American College of Surgeons
BACKGROUND: Surgical complications have tremendous consequences and costs. Complication detection is important for quality improvement, but traditional manual chart review is burdensome. Automated mechanisms are needed to make this more efficient. To...

Comparison Between Manual Auditing and a Natural Language Process With Machine Learning Algorithm to Evaluate Faculty Use of Standardized Reports in Radiology.

Journal of the American College of Radiology : JACR
PURPOSE: When implementing or monitoring department-sanctioned standardized radiology reports, feedback about individual faculty performance has been shown to be a useful driver of faculty compliance. Most commonly, these data are derived from manual...

Accelerating Chart Review Using Automated Methods on Electronic Health Record Data for Postoperative Complications.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Manual Chart Review (MCR) is an important but labor-intensive task for clinical research and quality improvement. In this study, aiming to accelerate the process of extracting postoperative outcomes from medical charts, we developed an automated post...

An audit of the impact of the introduction of a commercial artificial intelligence-driven auto-contouring tool into a radiotherapy department.

The British journal of radiology
OBJECTIVES: To audit prospectively the accuracy, time saving, and utility of a commercial artificial intelligence auto-contouring tool (AIAC). To assess the reallocation of time released by AIAC.

Machine learning to predict notes for chart review in the oncology setting: a proof of concept strategy for improving clinician note-writing.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Leverage electronic health record (EHR) audit logs to develop a machine learning (ML) model that predicts which notes a clinician wants to review when seeing oncology patients.

Concordance analysis of intrapartum cardiotocography between physicians and artificial intelligence-based technique using modified one-dimensional fully convolutional networks.

Journal of the Chinese Medical Association : JCMA
BACKGROUND: Cardiotocography is a common method of electronic fetal monitoring (EFM) for fetal well-being. Data-driven analyses have shown potential for automated EFM assessment. For this preliminary study, we used a novel artificial intelligence met...