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Decision Support Systems, Clinical

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Clinician and computer: a study on doctors' perceptions of artificial intelligence in skeletal radiography.

BMC medical education
BACKGROUND: Traumatic musculoskeletal injuries are a common presentation to emergency care, the first-line investigation often being plain radiography. The interpretation of this imaging frequently falls to less experienced clinicians despite well-es...

Digital Health: Today's Solutions and Tomorrow's Impact.

Clinics in laboratory medicine
Artificial intelligence (AI) is becoming an indispensable tool to augment decision making in different health care settings and by various members of the patient pathway, including the patient. AI provides the ability to optimize data to bring clinic...

Machine learning in the coagulation and hemostasis arena: an overview and evaluation of methods, review of literature, and future directions.

Journal of thrombosis and haemostasis : JTH
Artificial Intelligence and machine-learning (ML) studies are increasingly populating the life science space and some have also started to integrate certain clinical decision support tasks. However, most of the activities within this space understand...

Usability and Clinician Acceptance of a Deep Learning-Based Clinical Decision Support Tool for Predicting Glaucomatous Visual Field Progression.

Journal of glaucoma
PRCIS: We updated a clinical decision support tool integrating predicted visual field (VF) metrics from an artificial intelligence model and assessed clinician perceptions of the predicted VF metric in this usability study.

An Artificial Intelligence Tool for Clinical Decision Support and Protocol Selection for Brain MRI.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Protocolling, the process of determining the most appropriate acquisition parameters for an imaging study, is time-consuming and produces variable results depending on the performing physician. The purpose of this study was to...

Electronic Health Record Optimization for Artificial Intelligence.

Clinics in laboratory medicine
Laboratory clinical decision support (CDS) typically relies on data from the electronic health record (EHR). The implementation of a sustainable, effective laboratory CDS program requires a commitment to standardization and harmonization of key EHR d...

Clinical Artificial Intelligence: Design Principles and Fallacies.

Clinics in laboratory medicine
Clinical artificial intelligence (AI)/machine learning (ML) is anticipated to offer new abilities in clinical decision support, diagnostic reasoning, precision medicine, clinical operational support, and clinical research, but careful concern is need...

Artificial intelligence to support early diagnosis of temporomandibular disorders: A preliminary case study.

Journal of oral rehabilitation
BACKGROUND: Temporomandibular disorders (TMDs) are disabling conditions with a negative impact on the quality of life. Their diagnosis is a complex and multi-factorial process that should be conducted by experienced professionals, and most TMDs remai...

Developing an AI-assisted clinical decision support system to enhance in-patient holistic health care.

PloS one
Holistic health care (HHC) is a synonym for complete patient care, and as such an efficient clinical decision support system (CDSS) for HHC is critical to support the judgement of physician's decision in response of patient's physical, emotional, soc...