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Expanding interpretability through complexity reduction in machine learning-based modelling of cardiovascular disease: A myocardial perfusion imaging PET/CT prognostic study.

European journal of clinical investigation
BACKGROUND: Machine learning-based analysis can be used in myocardial perfusion imaging data to improve risk stratification and the prediction of major adverse cardiovascular events for patients with suspected or established coronary artery disease. ...

Free-breathing, Highly Accelerated, Single-beat, Multisection Cardiac Cine MRI with Generative Artificial Intelligence.

Radiology. Cardiothoracic imaging
Purpose To develop and evaluate a free-breathing, highly accelerated, multisection, single-beat cine sequence for cardiac MRI. Materials and Methods This prospective study, conducted from July 2022 to December 2023, included participants with various...

Suspicious of AI? Perceived autonomy and interdependence predict AI-related conspiracy beliefs.

The British journal of social psychology
As artificial intelligence (AI) evolves, conspiracy theories have emerged that authorities will use AI to oppress humanity, or AI itself will. We propose that perceived high autonomy and low interdependence of AI increase AI-related conspiracy belief...

Treatment of Porphyria Cutanea Tarda Scarring With Combination Laser Treatment and a Pilot Use of Artificial Intelligence to Quantify Laser Results.

Journal of cosmetic dermatology
BACKGROUND: Porphyria cutanea tarda (PCT) is the most common subtype of porphyria and results from a deficiency of the enzyme uroporphyrinogen decarboxylase. Even after successful treatment, patients can be left with significant scarring, and there i...

Determining health care cost drivers in older Hodgkin lymphoma survivors using interpretable machine learning methods.

Journal of managed care & specialty pharmacy
BACKGROUND: The cost of health care for patients with Hodgkin lymphoma (HL) is projected to rise, making it essential to understand expenditure drivers across different demographics, including the older adult population. Although older HL patients co...

Artificial Intelligence in Cardiac Rehabilitation: Assessing ChatGPT's Knowledge and Clinical Scenario Responses.

Turk Kardiyoloji Dernegi arsivi : Turk Kardiyoloji Derneginin yayin organidir
OBJECTIVE: Cardiac rehabilitation (CR) improves survival, reduces hospital readmissions, and enhances quality of life; however, participation remains low due to barriers related to access, awareness, and socioeconomic factors. This study explores the...

Deep Learning-Accelerated Non-Contrast Abbreviated Liver MRI for Detecting Malignant Focal Hepatic Lesions: Dual-Center Validation.

Korean journal of radiology
OBJECTIVE: To compare a deep learning (DL)-accelerated non-enhanced abbreviated MRI (AMRI) protocol with standard AMRI (AMRI) of the liver in terms of image quality and malignant focal lesion detection.

Understanding Public Judgements on Artificial Intelligence in Healthcare: Dialogue Group Findings From Australia.

Health expectations : an international journal of public participation in health care and health policy
INTRODUCTION: There is a rapidly increasing number of applications of healthcare artificial intelligence (HCAI). Alongside this, a new field of research is investigating public support for HCAI. We conducted a study to identify the conditions on Aust...

Electrocardiogram-based deep learning to predict left ventricular systolic dysfunction in paediatric and adult congenital heart disease in the USA: a multicentre modelling study.

The Lancet. Digital health
BACKGROUND: Left ventricular systolic dysfunction (LVSD) is independently associated with cardiovascular events in patients with congenital heart disease. Although artificial intelligence-enhanced electrocardiogram (AI-ECG) analysis is predictive of ...

Snapshot artificial intelligence-determination of ejection fraction from a single frame still image: a multi-institutional, retrospective model development and validation study.

The Lancet. Digital health
BACKGROUND: Artificial intelligence (AI) is poised to transform point-of-care practice by providing rapid snapshots of cardiac functioning. Although previous AI models have been developed to estimate left ventricular ejection fraction (LVEF), they ha...