AIMC Topic: Humans

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Effects of nerve-sparing procedures on surgical margins after robot-assisted radical prostatectomy.

Journal of the Chinese Medical Association : JCMA
BACKGROUND: Nerve-sparing (NS) techniques could potentially increase positive surgical margins after robot-assisted radical prostatectomy (RARP). Nevertheless, the available studies have revealed ambiguous results among distinct groups. This study pu...

The development and deployment of machine learning models.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Applications of artificial intelligence, specifically machine learning, are becoming increasingly popular in Orthopaedic Surgery, and medicine as a whole. This growing interest is shared by data scientists and physicians alike. However, there is an a...

Automated analysis of three-dimensional CBCT images taken in natural head position that combines facial profile processing and multiple deep-learning models.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Analyzing three-dimensional cone beam computed tomography (CBCT) images has become an indispensable procedure for diagnosis and treatment planning of orthodontic patients. Artificial intelligence, especially deep-learning t...

Efficient two-step liver and tumour segmentation on abdominal CT via deep learning and a conditional random field.

Computers in biology and medicine
Segmentation of the liver and tumours from computed tomography (CT) scans is an important task in hepatic surgical planning. Manual segmentation of the liver and tumours is a time-consuming and labour-intensive task; therefore, a fully automated meth...

Machine learning approaches used to analyze auditory evoked responses from the human auditory brainstem: A systematic review.

Computer methods and programs in biomedicine
BACKGROUND: The application of machine learning algorithms for assessing the auditory brainstem response has gained interest over recent years with a considerable number of publications in the literature. In this systematic review, we explore how mac...

Enhanced artificial intelligence for electrochemical sensors in monitoring and removing of azo dyes and food colorant substances.

Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association
It is necessary to determine whether synthetic dyes are present in food since their excessive use has detrimental effects on human health. For the simultaneous assessment of tartrazine and Patent Blue V, a novel electrochemical sensing platform was d...

Implementation of Machine Learning to Predict Cost of Care Associated with Ambulatory Single-Level Lumbar Decompression.

World neurosurgery
BACKGROUND: With the emergence of the concept of value-based care, efficient resource allocation has become an increasingly prominent factor in surgical decision-making. Validated machine learning (ML) models for cost prediction in outpatient spine s...

Adverse events in the digital age and where to find them.

Pharmacoepidemiology and drug safety
Exponential growth of health-related data collected by digital tools is a reality within pharmaceutical and medical device research and development. Data generated through digital tools may be categorized as relevant to efficacy and/or safety. The en...

FHIR-Ontop-OMOP: Building clinical knowledge graphs in FHIR RDF with the OMOP Common data Model.

Journal of biomedical informatics
BACKGROUND: Knowledge graphs (KGs) play a key role to enable explainable artificial intelligence (AI) applications in healthcare. Constructing clinical knowledge graphs (CKGs) against heterogeneous electronic health records (EHRs) has been desired by...

Development of comprehensive annotation criteria for patients' states from clinical texts.

Journal of biomedical informatics
In clinical records, much of the clinical information is recorded as free text, thus necessitating the use of advanced automatic information extraction technology. The development of practical technologies requires a corpus with finer granularity ann...