Medicolegal

Natural Language Processing: Practical Applications in Medicine and Investigation of Contextual Autocomplete.

Natural language processing (NLP) is the task of converting unstructured human language data into st...

Demystifying Medico-legal Challenges of Artificial Intelligence Applications in Molecular Imaging and Therapy.

Artificial Intelligence (AI) has been rapidly embraced by imaging fields and offers a variety of ben...

Artificial Intelligence and Positron Emission Tomography Imaging Workflow:: Technologists' Perspective.

Artificial intelligence (AI) can enhance the efficiency of medical imaging quality control and clini...

Applying a Common Enterprise Theory of Liability to Clinical AI Systems.

The advent of artificial intelligence ("AI") holds great potential to improve clinical diagnostics. ...

Realizing the Power of Text Mining and Natural Language Processing for Analyzing Patient Safety Event Narratives: The Challenges and Path Forward.

Patient safety event (PSE) reports are a useful lens to understand hazards and patient safety risks ...

The difficult role of Artificial Intelligence in Medical Liability: to err is not only human.

The entrance of Artificial Intelligence (AI) as a new actor in the doctor-patient relationship has e...

A comparative study of AI systems for epileptic seizure recognition based on EEG or ECG.

The majority of studies for automatic epileptic seizure (ictal) detection are based on electroenceph...

Deep and accurate detection of m6A RNA modifications using miCLIP2 and m6Aboost machine learning.

N6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic mRNAs and infl...

Histograms of Frequency-Intensity Distribution Deep Learning to Predict the Seizure Liability of Drugs in Electroencephalography.

Detection of seizures as well as that of seizure auras is effective in improving the predictive accu...

Public vs physician views of liability for artificial intelligence in health care.

The growing use of artificial intelligence (AI) in health care has raised questions about who should...

Deep Neural Network Driven Speech Classification for Relevance Detection in Automatic Medical Documentation.

The automation of medical documentation is a highly desirable process, especially as it could avert ...

ARTIFICIAL INTELLIGENCE IN MEDICAL DEVICES: PAST, PRESENT AND FUTURE.

Artificial Intelligence (AI) has been drawing attention in the field of medical devices. However, du...

Natural Language Processing to Assess Frequency of Functional Status Documentation for Patients Newly Diagnosed With Colorectal Cancer.

Natural Language Processing to Assess Frequency of Functional Status Documentation for Patients Newly Diagnosed With Colorectal Cancer-Reply.

Natural Language Processing to Assess Frequency of Functional Status Documentation for Patients Newly Diagnosed With Colorectal Cancer.

Classifying Pseudogout Using Machine Learning Approaches With Electronic Health Record Data.

OBJECTIVE: Identifying pseudogout in large data sets is difficult due to its episodic nature and a l...

The Gene Ontology resource: enriching a GOld mine.

The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for ...

Artificial intelligence in cancer diagnostics and therapy: current perspectives.

Artificial intelligence (AI) has found its way into every sphere of human life including the field o...

Unexpected Inequality: Disparate-Impact From Artificial Intelligence in Healthcare Decisions.

Systemic discrimination in healthcare plagues marginalized groups. Physicians incorrectly view peopl...

Artificial Intelligence in the Healthcare System: An Overview.

This chapter aims to present insights into the influence of artificial intelligence (AI) on medicine...

Rhabdomyolysis in a Civil Aviation Pilot.

Rhabdomyolysis is a potentially fatal disease caused by trauma, infections, and toxins. Rhabdomyoly...