AIMC Topic: Quality Indicators, Health Care

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Machine learning-based prediction of heart failure readmission or death: implications of choosing the right model and the right metrics.

ESC heart failure
AIMS: Machine learning (ML) is widely believed to be able to learn complex hidden interactions from the data and has the potential in predicting events such as heart failure (HF) readmission and death. Recent studies have revealed conflicting results...

Automatic Classification of Online Doctor Reviews: Evaluation of Text Classifier Algorithms.

Journal of medical Internet research
BACKGROUND: An increasing number of doctor reviews are being generated by patients on the internet. These reviews address a diverse set of topics (features), including wait time, office staff, doctor's skills, and bedside manners. Most previous work ...

Natural Language Processing Accurately Calculates Adenoma and Sessile Serrated Polyp Detection Rates.

Digestive diseases and sciences
BACKGROUND: ADR is a widely used colonoscopy quality indicator. Calculation of ADR is labor-intensive and cumbersome using current electronic medical databases. Natural language processing (NLP) is a method used to extract meaning from unstructured o...

Agility assessment using fuzzy logic approach: a case of healthcare dispensary.

BMC health services research
BACKGROUND: Agile concepts are not only beneficial for manufacturing sector but also for service sector such as healthcare. However, assessment of agility has been predominantly done in manufacturing enterprises. This study demonstrates a means to me...

Assessing Hospital Performance After Percutaneous Coronary Intervention Using Big Data.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: Although risk adjustment remains a cornerstone for comparing outcomes across hospitals, optimal strategies continue to evolve in the presence of many confounders. We compared conventional regression-based model to approaches particularly ...

Natural language processing as an alternative to manual reporting of colonoscopy quality metrics.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: The adenoma detection rate (ADR) is a quality metric tied to interval colon cancer occurrence. However, manual extraction of data to calculate and track the ADR in clinical practice is labor-intensive. To overcome this difficulty...

Semantic Convergence with LLMs for Head and Neck Cancer Quality Indicators.

Studies in health technology and informatics
We developed a novel method for leveraging large language models (LLM) to systematically filter and categorize large numbers of clinical quality indicators (CQI) for head and neck cancer. This was used to transform a tedious, human-resource intensive...

Estimating the incubated river water quality indicator based on machine learning and deep learning paradigms: BOD5 Prediction.

Mathematical biosciences and engineering : MBE
As an indicator measured by incubating organic material from water samples in rivers, the most typical characteristic of water quality items is biochemical oxygen demand (BOD) concentration, which is a stream pollutant with an extreme circumstance of...

Machine Learning for Health Services Researchers.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
BACKGROUND: Machine learning is increasingly used to predict healthcare outcomes, including cost, utilization, and quality.