AI Medical Compendium Journal:
The Lancet. Digital health

Showing 11 to 20 of 256 articles

ChatGPT for digital pathology research.

The Lancet. Digital health
The rapid evolution of generative artificial intelligence (AI) models including OpenAI's ChatGPT signals a promising era for medical research. In this Viewpoint, we explore the integration and challenges of large language models (LLMs) in digital pat...

A deep learning-based model to estimate pulmonary function from chest x-rays: multi-institutional model development and validation study in Japan.

The Lancet. Digital health
BACKGROUND: Chest x-ray is a basic, cost-effective, and widely available imaging method that is used for static assessments of organic diseases and anatomical abnormalities, but its ability to estimate dynamic measurements such as pulmonary function ...

Deep learning models for thyroid nodules diagnosis of fine-needle aspiration biopsy: a retrospective, prospective, multicentre study in China.

The Lancet. Digital health
BACKGROUND: Accurately distinguishing between malignant and benign thyroid nodules through fine-needle aspiration cytopathology is crucial for appropriate therapeutic intervention. However, cytopathologic diagnosis is time consuming and hindered by t...

Ethical and regulatory challenges of large language models in medicine.

The Lancet. Digital health
With the rapid growth of interest in and use of large language models (LLMs) across various industries, we are facing some crucial and profound ethical concerns, especially in the medical field. The unique technical architecture and purported emergen...

Artificial intelligence-based models enabling accurate diagnosis of ovarian cancer using laboratory tests in China: a multicentre, retrospective cohort study.

The Lancet. Digital health
BACKGROUND: Ovarian cancer is the most lethal gynecological malignancy. Timely diagnosis of ovarian cancer is difficult due to the lack of effective biomarkers. Laboratory tests are widely applied in clinical practice, and some have shown diagnostic ...

Deep learning for [F]fluorodeoxyglucose-PET-CT classification in patients with lymphoma: a dual-centre retrospective analysis.

The Lancet. Digital health
BACKGROUND: The rising global cancer burden has led to an increasing demand for imaging tests such as [F]fluorodeoxyglucose ([F]FDG)-PET-CT. To aid imaging specialists in dealing with high scan volumes, we aimed to train a deep learning artificial in...

Development and validation of open-source deep neural networks for comprehensive chest x-ray reading: a retrospective, multicentre study.

The Lancet. Digital health
BACKGROUND: Artificial intelligence (AI) systems for automated chest x-ray interpretation hold promise for standardising reporting and reducing delays in health systems with shortages of trained radiologists. Yet, there are few freely accessible AI s...