AIMC Topic: Diagnosis, Computer-Assisted

Clear Filters Showing 1561 to 1570 of 1778 articles

Application of Pre-Trained Deep Learning Models for Clinical ECGs.

Studies in health technology and informatics
Automatic electrocardiogram (ECG) analysis has been one of the very early use cases for computer assisted diagnosis (CAD). Most ECG devices provide some level of automatic ECG analysis. In the recent years, Deep Learning (DL) is increasingly used for...

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...

Future artificial intelligence tools and perspectives in medicine.

Current opinion in urology
PURPOSE OF REVIEW: Artificial intelligence has become popular in medical applications, specifically as a clinical support tool for computer-aided diagnosis. These tools are typically employed on medical data (i.e., image, molecular data, clinical var...

How machine learning is impacting research in atrial fibrillation: implications for risk prediction and future management.

Cardiovascular research
There has been an exponential growth of artificial intelligence (AI) and machine learning (ML) publications aimed at advancing our understanding of atrial fibrillation (AF), which has been mainly driven by the confluence of two factors: the advances ...

Multimodal, multitask, multiattention (M3) deep learning detection of reticular pseudodrusen: Toward automated and accessible classification of age-related macular degeneration.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Reticular pseudodrusen (RPD), a key feature of age-related macular degeneration (AMD), are poorly detected by human experts on standard color fundus photography (CFP) and typically require advanced imaging modalities such as fundus autoflu...

Synthetic data in machine learning for medicine and healthcare.

Nature biomedical engineering
The proliferation of synthetic data in artificial intelligence for medicine and healthcare raises concerns about the vulnerabilities of the software and the challenges of current policy.

Deep learning-based artificial intelligence model to assist thyroid nodule diagnosis and management: a multicentre diagnostic study.

The Lancet. Digital health
BACKGROUND: Strategies for integrating artificial intelligence (AI) into thyroid nodule management require additional development and testing. We developed a deep-learning AI model (ThyNet) to differentiate between malignant tumours and benign thyroi...