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Automated generation of echocardiography reports using artificial intelligence: a novel approach to streamlining cardiovascular diagnostics.

The international journal of cardiovascular imaging
Accurate interpretation of echocardiography measurements is essential for diagnosing cardiovascular diseases and guiding clinical management. The emergence of large language models (LLMs) like ChatGPT presents a novel opportunity to automate the gene...

AI-ECG Supported Decision-Making for Coronary Angiography in Acute Chest Pain: The QCG-AID Study.

Journal of Korean medical science
This pilot study evaluates an artificial intelligence (AI)-assisted electrocardiography (ECG) analysis system, QCG, to enhance urgent coronary angiography (CAG) decision-making for acute chest pain in the emergency department (ED). We retrospectively...

Harness machine learning for multiple prognoses prediction in sepsis patients: evidence from the MIMIC-IV database.

BMC medical informatics and decision making
BACKGROUND: Sepsis, a severe systemic response to infection, frequently results in adverse outcomes, underscoring the urgency for prompt and accurate prognostic tools. Machine learning methods such as logistic regression, random forests, and CatBoost...

Gd-EOB-DTPA-enhanced MRI radiomics and deep learning models to predict microvascular invasion in hepatocellular carcinoma: a multicenter study.

BMC medical imaging
BACKGROUND: Microvascular invasion (MVI) is an important risk factor for early postoperative recurrence of hepatocellular carcinoma (HCC). Based on gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance ...

Detection of antibodies in suspected autoimmune encephalitis diseases using machine learning.

Scientific reports
In our study, we aim to predict the antibody serostatus of patients with suspected autoimmune encephalitis (AE) using machine learning based on pre-contrast T2-weighted MR images acquired at symptom onset. A confirmation of seropositivity is of great...

Machine learning models for pancreatic cancer diagnosis based on microbiome markers from serum extracellular vesicles.

Scientific reports
Pancreatic cancer (PC) is a fatal disease with an extremely low 5-year survival rate, mainly because of its poor detection rate in early stages. Given emerging evidence of the relationship between microbiota composition and diseases, this study aims ...

Clinical implications of deep learning based image analysis of whole radical prostatectomy specimens.

Scientific reports
Prostate cancer (PCa) diagnosis faces significant challenges due to its complex pathological characteristics and insufficient pathologist resources. While deep learning-based image analysis (DLIA) shows promise in enhancing diagnostic accuracy, its a...

People are poorly equipped to detect AI-powered voice clones.

Scientific reports
As generative artificial intelligence (AI) continues its ballistic trajectory, everything from text to audio, image, and video generation continues to improve at mimicking human-generated content. Through a series of perceptual studies, we report on ...

Integrating deep learning with ECG, heart rate variability and demographic data for improved detection of atrial fibrillation.

Open heart
BACKGROUND: Atrial fibrillation (AF) is a common but often undiagnosed condition, increasing the risk of stroke and heart failure. Early detection is crucial, yet traditional methods struggle with AF's transient nature. This study investigates how au...