In this paper, we discuss how to utilize the co-occurrence of answers in building an automatic question answering system that answers a series of questions on a specific topic in a batch mode. Experiments show that the answers to the many of the questions in the series usually have a high degree of co-occurrence in relevant document passages. This feature sometimes can’t be easily utilized in a...

Factoid question answering (QA) has recently benefited from the development of deep learning (DL) systems. Neural network models outperform traditional approaches in domains where large datasets exist, such as SQuAD (≈ 100, 000 questions) for Wikipedia articles. However, these systems have not yet been applied to QA in more specific domains, such as biomedicine, because datasets are generally t...

Introduction: Electronic portal imaging devices (EPIDs) provide two- and three-dimensional planar and volumetric cone beam images to improve the accuracy of radiation treatment delivery. Periodic quality assurance (QA) of EPIDs is essential for dosimetric verification in radiotherapy. In this study, a QA program was implemented to evaluate the function of the EPID to be confident in applying co...

PURPOSE The purpose of this guideline is to provide a list of critical performance tests in order to assist the Qualified Medical Physicist (QMP) in establishing and maintaining a safe and effective quality assurance (QA) program. The performance tests on a linear accelerator (linac) should be selected to fit the clinical patterns of use of the accelerator and care should be given to perform te...

Electronic medical records (EMRs) document the healthcare provided to the patient using both unstructured clinical notes and structured data. Typically, these records are large, containing hundreds of documents about a single patient. To navigate the vast amounts of information about a patient, current EMR applications available to physicians either attempt to proactively summarize important pa...

OBJECTIVES In this survey, we reviewed the current state of the art in biomedical QA (Question Answering), within a broader framework of semantic knowledge-based QA approaches, and projected directions for the future research development in this critical area of intersection between Artificial Intelligence, Information Retrieval, and Biomedical Informatics. MATERIALS AND METHODS We devised a ...

We introduce a probabilistic noisychannel model for question answering and we show how it can be exploited in the context of an end-to-end QA system. Our noisy-channel system outperforms a stateof-the-art rule-based QA system that uses similar resources. We also show that the model we propose is flexible enough to accommodate within one mathematical framework many QA-specific resources and tech...