AIMC Topic: Artificial Intelligence

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

Toxicological sciences : an official journal of the Society of Toxicology
Detection of seizures as well as that of seizure auras is effective in improving the predictive accuracy of seizure liability of drugs. Whereas electroencephalography has been known to be effective for the detection of seizure liability, no establish...

Quantitative Assessment of Fundus Tessellated Density and Associated Factors in Fundus Images Using Artificial Intelligence.

Translational vision science & technology
PURPOSE: This study aimed to quantitative assess the fundus tessellated density (FTD) and associated factors on the basis of fundus photographs using artificial intelligence.

Deep Learning for Automated Diabetic Retinopathy Screening Fused With Heterogeneous Data From EHRs Can Lead to Earlier Referral Decisions.

Translational vision science & technology
PURPOSE: Fundus images are typically used as the sole training input for automated diabetic retinopathy (DR) classification. In this study, we considered several well-known DR risk factors and attempted to improve the accuracy of DR screening.

[Deep Learning-Based Cardiac Imaging Data Measurement and Its Application in Diagnosis of Sudden Cardiac Death].

Fa yi xue za zhi
In the field of forensic medicine, diagnosis of sudden cardiac death is limited by subjective factors and manual measurement methods, so some parameters may have estimation deviation or measurement deviation. As postmortem CT imaging plays a more and...

Interest in artificial intelligence for the diagnosis of non-melanoma skin cancer: a survey among French general practitioners.

European journal of dermatology : EJD
General practitioners (GPs) are playing a key role in skin cancer screening. Non-melanoma skin cancer is frequent and difficult to diagnose. We aimed to assess whether GPs are facing difficulties in diagnosing non-pigmented skin tumours (NPSTs) and w...

Early Detection of Pancreatic Cancer: Applying Artificial Intelligence to Electronic Health Records.

Pancreas
The potential of artificial intelligence (AI) applied to clinical data from electronic health records (EHRs) to improve early detection for pancreatic and other cancers remains underexplored. The Kenner Family Research Fund, in collaboration with the...

Learn to synchronize, synchronize to learn.

Chaos (Woodbury, N.Y.)
In recent years, the artificial intelligence community has seen a continuous interest in research aimed at investigating dynamical aspects of both training procedures and machine learning models. Of particular interest among recurrent neural networks...

Review of study reporting guidelines for clinical studies using artificial intelligence in healthcare.

BMJ health & care informatics
High-quality research is essential in guiding evidence-based care, and should be reported in a way that is reproducible, transparent and where appropriate, provide sufficient detail for inclusion in future meta-analyses. Reporting guidelines for vari...

Rapid Exclusion of COVID Infection With the Artificial Intelligence Electrocardiogram.

Mayo Clinic proceedings
OBJECTIVE: To rapidly exclude severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using artificial intelligence applied to the electrocardiogram (ECG).