AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Tomography, X-Ray Computed

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Reconstructing and analyzing the invariances of low-dose CT image denoising networks.

Medical physics
BACKGROUND: Deep learning-based methods led to significant advancements in many areas of medical imaging, most of which are concerned with the reduction of artifacts caused by motion, scatter, or noise. However, with most neural networks being black ...

Personalized prediction of immunotherapy response in lung cancer patients using advanced radiomics and deep learning.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Lung cancer (LC) is a leading cause of cancer-related mortality, and immunotherapy (IO) has shown promise in treating advanced-stage LC. However, identifying patients likely to benefit from IO and monitoring treatment response remains cha...

Sex estimation using skull silhouette images from postmortem computed tomography by deep learning.

Scientific reports
Prompt personal identification is required during disasters that can result in many casualties. To rapidly estimate sex based on skull structure, this study applied deep learning using two-dimensional silhouette images, obtained from head postmortem ...

Efficacy of automated machine learning models and feature engineering for diagnosis of equivocal appendicitis using clinical and computed tomography findings.

Scientific reports
This study evaluates the diagnostic efficacy of automated machine learning (AutoGluon) with automated feature engineering and selection (autofeat), focusing on clinical manifestations, and a model integrating both clinical manifestations and CT findi...

A vision transformer-based deep transfer learning nomogram for predicting lymph node metastasis in lung adenocarcinoma.

Medical physics
BACKGROUND: Lymph node metastasis (LNM) plays a crucial role in the management of lung cancer; however, the ability of chest computed tomography (CT) imaging to detect LNM status is limited.

Impact of artificial intelligence assistance on pulmonary nodule detection and localization in chest CT: a comparative study among radiologists of varying experience levels.

Scientific reports
The study aimed to evaluate the impact of AI assistance on pulmonary nodule detection rates among radiology residents and senior radiologists, along with assessing the effectiveness of two different commercialy available AI software systems in improv...

Label refinement network from synthetic error augmentation for medical image segmentation.

Medical image analysis
Deep convolutional neural networks for image segmentation do not learn the label structure explicitly and may produce segmentations with an incorrect structure, e.g., with disconnected cylindrical structures in the segmentation of tree-like structure...

Using 3D point cloud and graph-based neural networks to improve the estimation of pulmonary function tests from chest CT.

Computers in biology and medicine
Pulmonary function tests (PFTs) are important clinical metrics to measure the severity of interstitial lung disease for systemic sclerosis patients. However, PFTs cannot always be performed by spirometry if there is a risk of disease transmission or ...

An open-source fine-tuned large language model for radiological impression generation: a multi-reader performance study.

BMC medical imaging
BACKGROUND: The impression section integrates key findings of a radiology report but can be subjective and variable. We sought to fine-tune and evaluate an open-source Large Language Model (LLM) in automatically generating impressions from the remain...