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Artificial intelligence in radiology decision support systems

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Post on 2019-6-5 12:08:56 | All posts |Read mode
Radiologists employ artificial intelligence (AI) techniques that allow computers to emulate human faculties such as perception and reasoning in the task of diagnosing disease, AI offers a major opportunity to enhance and augment radiology reading, The most common AI tools used for decision support include Bayesian networks, neural networks, case-based reasoning, and rule-based systems.
It is very difficult or impossible to go through large volumes of data to pick out what is clinically relevant or actionable, It is easy for things to fall through the cracks or for things to be lost to patient follow-up, This issue is further compounded when you add factors like increasing patient volumes, lower reimbursements, bundled payments and the conversion from fee-for-service to a fee-for-value reimbursement system, This information would take too long to collect, or its existence might not be known, by the physician so they would not have spent time looking for it.
Computer-based systems that incorporate artificial intelligence techniques are used in decision support systems, Artificial intelligence (also called deep learning, machine learning or artificial neural networks) use cases for medical imaging, It can present a paradigm shift in how clinicians work in an effort to boost workflow efficiency, while at the same time improving patients' care.
Automated pulmonary artery flow quantification would save the interpreting physician time via elimination of manual measurements, prevent detection errors, and provide structured quantitative data, which could be used in later studies or risk stratification schemes.
It is very difficult to go through large volumes of data to pick out what is clinically relevant or actionable, It is easy for things to be lost due to patient follow-up, This issue is further compounded when you add factors like increasing patient data volumes, lower reimbursements, bundled payments and the conversion from fee-for-service to a fee-for-value reimbursement system.
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Science Online

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