Surveillance

Diagnostic performance of an artificial intelligence-driven cardiac-structured reporting system for myocardial perfusion SPECT imaging.

OBJECTIVES: To describe and validate an artificial intelligence (AI)-driven structured reporting system by direct comparison of automatically generated reports to results from actual clinical reports generated by nuclear cardiology experts.

The Elephant in the Room: Outbreak of Carfentanil Deaths in Minnesota and the Importance of Multiagency Collaboration.

Over a three-month period in early 2017, the Hennepin County Medical Examiner's Office investigated nine apparent opioid toxicity deaths that occurred in three separate urban, suburban, and rural counties in our jurisdiction. All decedents were known substance abusers and had reportedly recently used heroin; most were found with drug paraphernalia. Complete autopsies variably showed classic stigma...

Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease.

Prognostic modelling is important in clinical practice and epidemiology for patient management and research. Electronic health records (EHR) provide l...

Artificial Intelligence in Public Health and Epidemiology.

OBJECTIVES:  To introduce and summarize current research in the field of Public Health and Epidemiology Informatics.

Management practices associated with strongylid parasite prevalence on horse farms in rural counties of Kentucky.

Anthelmintic resistance among cyathostomin parasites is a wide-spread problem. The parasite control guidelines written by the American Association of ...

Automated deep-neural-network surveillance of cranial images for acute neurologic events.

Rapid diagnosis and treatment of acute neurological illnesses such as stroke, hemorrhage, and hydrocephalus are critical to achieving positive outcome...

Mining heterogeneous networks with topological features constructed from patient-contributed content for pharmacovigilance.

Drug safety, also called pharmacovigilance, represents a serious health problem all over the world. Adverse drug reactions (ADRs) and drug-drug intera...

Predicting Infectious Disease Using Deep Learning and Big Data.

Infectious disease occurs when a person is infected by a pathogen from another person or an animal. It is a problem that causes harm at both individua...

Natural Language Processing and Its Implications for the Future of Medication Safety: A Narrative Review of Recent Advances and Challenges.

The safety of medication use has been a priority in the United States since the late 1930s. Recently, it has gained prominence due to the increasing a...

A machine learning method to monitor China's AIDS epidemics with data from Baidu trends.

BACKGROUND: AIDS is a worrying public health issue in China and lacks timely and effective surveillance. With the diffusion and adoption of the Intern...

Granulomatosis with polyangiitis in Northeastern Brazil: study of 25 cases and review of the literature.

BACKGROUND: Little has been published about the epidemiology of Granulomatosis with polyangiitis (GPA) in South America, especially in the intertropic...

Acute pain intensity monitoring with the classification of multiple physiological parameters.

Current acute pain intensity assessment tools are mainly based on self-reporting by patients, which is impractical for non-communicative, sedated or c...

UAVs, Hyperspectral Remote Sensing, and Machine Learning Revolutionizing Reef Monitoring.

Recent advances in unmanned aerial system (UAS) sensed imagery, sensor quality/size, and geospatial image processing can enable UASs to rapidly and co...

The past, present and future role of artificial intelligence in imaging.

Artificial intelligence (AI) is already widely employed in various medical roles, and ongoing technological advances are encouraging more widespread u...

Automatic classification of radiological reports for clinical care.

Radiological reporting generates a large amount of free-text clinical narratives, a potentially valuable source of information for improving clinical ...

A comparison of statistical and machine-learning techniques in evaluating the association between dietary patterns and 10-year cardiometabolic risk (2002-2012): the ATTICA study.

Statistical methods are usually applied in examining diet-disease associations, whereas factor analysis is commonly used for dietary pattern recogniti...

Sarcopenia: Beyond Muscle Atrophy and into the New Frontiers of Opportunistic Imaging, Precision Medicine, and Machine Learning.

As populations continue to age worldwide, the impact of sarcopenia on public health will continue to grow. The clinically relevant and increasingly co...

Structured radiology reporting on an institutional level-benefit or new administrative burden?

Significant technical advances have been made in radiology since the first discovery of X-rays. Diagnostic techniques have become more and more comple...

Machine learning identifies signatures of host adaptation in the bacterial pathogen Salmonella enterica.

Emerging pathogens are a major threat to public health, however understanding how pathogens adapt to new niches remains a challenge. New methods are u...

Deep generative learning for automated EHR diagnosis of traditional Chinese medicine.

BACKGROUND: Computer-aided medical decision-making (CAMDM) is the method to utilize massive EMR data as both empirical and evidence support for the de...