AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

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Deep Learning Models for Health and Safety Risk Prediction in Power Infrastructure Projects.

Risk analysis : an official publication of the Society for Risk Analysis
Inappropriate management of health and safety (H&S) risk in power infrastructure projects can result in occupational accidents and equipment damage. Accidents at work have detrimental effects on workers, company, and the general public. Despite the a...

Natural language processing for disease phenotyping in UK primary care records for research: a pilot study in myocardial infarction and death.

Journal of biomedical semantics
BACKGROUND: Free text in electronic health records (EHR) may contain additional phenotypic information beyond structured (coded) information. For major health events - heart attack and death - there is a lack of studies evaluating the extent to which...

Finding relevant free-text radiology reports at scale with IBM Watson Content Analytics: a feasibility study in the UK NHS.

Journal of biomedical semantics
BACKGROUND: Significant amounts of health data are stored as free-text within clinical reports, letters, discharge summaries and notes. Busy clinicians have limited time to read such large amounts of free-text and are at risk of information overload ...

Next generation pathology: artificial intelligence enhances histopathology practice.

The Journal of pathology
Deep learning algorithms have shown benefits for pathology in the context of risk stratification of tumors. Although the results are promising, several steps have to be made to confirm clinical utility. In a recent issue of The Journal of Pathology, ...

Artificial intelligence in clinical imaging: a health system approach.

Clinical radiology
The development and application of artificial intelligence (AI) to radiology requires an approach that encompasses a health system. The UK government and National Health Service (NHS) are creating an ecosystem to facilitate academic/industrial partne...

A validated natural language processing algorithm for brain imaging phenotypes from radiology reports in UK electronic health records.

BMC medical informatics and decision making
BACKGROUND: Manual coding of phenotypes in brain radiology reports is time consuming. We developed a natural language processing (NLP) algorithm to enable automatic identification of brain imaging in radiology reports performed in routine clinical pr...

The risks of risk. Regulating the use of machine learning for psychosis prediction.

International journal of law and psychiatry
Recent advances in Machine Learning (ML) have the potential to revolutionise psychosis prediction and psychiatric assessment. This article has two objectives. First, it clarifies which aspects of English Law are relevant in order to regulate the use ...

Implementation of a cloud-based referral platform in ophthalmology: making telemedicine services a reality in eye care.

The British journal of ophthalmology
BACKGROUND: Hospital Eye Services (HES) in the UK face an increasing number of optometric referrals driven by progress in retinal imaging. The National Health Service (NHS) published a 10-year strategy (NHS Long-Term Plan) to transform services to me...

Improving Workflow Efficiency for Mammography Using Machine Learning.

Journal of the American College of Radiology : JACR
OBJECTIVE: The aim of this study was to determine whether machine learning could reduce the number of mammograms the radiologist must read by using a machine-learning classifier to correctly identify normal mammograms and to select the uncertain and ...