AI Medical Compendium Topic:
Clinical Decision-Making

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Identification of Long Bone Fractures in Radiology Reports Using Natural Language Processing to support Healthcare Quality Improvement.

Applied clinical informatics
BACKGROUND: Important information to support healthcare quality improvement is often recorded in free text documents such as radiology reports. Natural language processing (NLP) methods may help extract this information, but these methods have rarely...

A clinical decision-making mechanism for context-aware and patient-specific remote monitoring systems using the correlations of multiple vital signs.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: In home-based context-aware monitoring patient's real-time data of multiple vital signs (e.g. heart rate, blood pressure) are continuously generated from wearable sensors. The changes in such vital parameters are highly cor...

Decision Making Based on Fuzzy Aggregation Operators for Medical Diagnosis from Dental X-ray images.

Journal of medical systems
Medical diagnosis is considered as an important step in dentistry treatment which assists clinicians to give their decision about diseases of a patient. It has been affirmed that the accuracy of medical diagnosis, which is much influenced by the clin...

Decision-Making Model for Adaptive Impedance Control of Teleoperation Systems.

IEEE transactions on haptics
This paper presents a haptic assistance strategy for teleoperation that makes a task and situation-specific compromise between improving tracking performance or human-machine interaction in partially structured environments via the scheduling of the ...

Using machine learning to support healthcare professionals in making preauthorisation decisions.

International journal of medical informatics
BACKGROUND: Preauthorisation is a control mechanism that is used by Health Insurance Providers (HIPs) to minimise wastage of resources through the denial of the procedures that were unduly requested. However, an efficient preauthorisation process req...

An international observational study suggests that artificial intelligence for clinical decision support optimizes anemia management in hemodialysis patients.

Kidney international
Managing anemia in hemodialysis patients can be challenging because of competing therapeutic targets and individual variability. Because therapy recommendations provided by a decision support system can benefit both patients and doctors, we evaluated...

Normal tissue complication probability (NTCP) modelling using spatial dose metrics and machine learning methods for severe acute oral mucositis resulting from head and neck radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Severe acute mucositis commonly results from head and neck (chemo)radiotherapy. A predictive model of mucositis could guide clinical decision-making and inform treatment planning. We aimed to generate such a model using spatia...

Pharmacogenomic knowledge representation, reasoning and genome-based clinical decision support based on OWL 2 DL ontologies.

BMC medical informatics and decision making
BACKGROUND: Every year, hundreds of thousands of patients experience treatment failure or adverse drug reactions (ADRs), many of which could be prevented by pharmacogenomic testing. However, the primary knowledge needed for clinical pharmacogenomics ...

Clinical time series prediction: Toward a hierarchical dynamical system framework.

Artificial intelligence in medicine
OBJECTIVE: Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventi...