AIMC Topic: Reproducibility of Results

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Automation, machine learning, and artificial intelligence in echocardiography: A brave new world.

Echocardiography (Mount Kisco, N.Y.)
Automation, machine learning, and artificial intelligence (AI) are changing the landscape of echocardiography providing complimentary tools to physicians to enhance patient care. Multiple vendor software programs have incorporated automation to impro...

Using natural language processing for identification of herpes zoster ophthalmicus cases to support population-based study.

Clinical & experimental ophthalmology
IMPORTANCE: Diagnosis codes are inadequate for accurately identifying herpes zoster (HZ) ophthalmicus (HZO). There is significant lack of population-based studies on HZO due to the high expense of manual review of medical records.

Evaluation of the VITEK MS knowledge base version 3.0 for the identification of clinically relevant Mycobacterium species.

Emerging microbes & infections
Different Mycobacterium spp. infections may indicate varied treatment regimens in the clinic. Thus, the species-level identification of Mycobacterium spp. is one of the most important tasks for a clinical microbiology laboratory. Although matrix-assi...

Assessment of the Feasibility of automated, real-time clinical decision support in the emergency department using electronic health record data.

BMC emergency medicine
BACKGROUND: The use of big data and machine learning within clinical decision support systems (CDSSs) has the potential to transform medicine through better prognosis, diagnosis and automation of tasks. Real-time application of machine learning algor...

Network-based association analysis to infer new disease-gene relationships using large-scale protein interactions.

PloS one
Protein-protein interactions integrated with disease-gene associations represent important information for revealing protein functions under disease conditions to improve the prevention, diagnosis, and treatment of complex diseases. Although several ...

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

Journal of clinical monitoring and computing
Current acute pain intensity assessment tools are mainly based on self-reporting by patients, which is impractical for non-communicative, sedated or critically ill patients. In previous studies, various physiological signals have been observed qualit...

An Algorithm Based on Deep Learning for Predicting In-Hospital Cardiac Arrest.

Journal of the American Heart Association
BACKGROUND: In-hospital cardiac arrest is a major burden to public health, which affects patient safety. Although traditional track-and-trigger systems are used to predict cardiac arrest early, they have limitations, with low sensitivity and high fal...

A novel integrated action crossing method for drug-drug interaction prediction in non-communicable diseases.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Drug-drug interaction (DDI) is one of the main causes of toxicity and treatment inefficacy. This work focuses on non-communicable diseases (NCDs), the non-transmissible and long-lasting diseases since they are the leading ca...

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

European journal of radiology
Artificial intelligence (AI) is already widely employed in various medical roles, and ongoing technological advances are encouraging more widespread use of AI in imaging. This is partly driven by the recognition of the significant frequency and clini...