AI Medical Compendium Topic:
Tomography, X-Ray Computed

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Artificial intelligence in COPD CT images: identification, staging, and quantitation.

Respiratory research
Chronic obstructive pulmonary disease (COPD) stands as a significant global health challenge, with its intricate pathophysiological manifestations often demanding advanced diagnostic strategies. The recent applications of artificial intelligence (AI)...

Artificial Intelligence-Based Classification of CT Images Using a Hybrid SpinalZFNet.

Interdisciplinary sciences, computational life sciences
The kidney is an abdominal organ in the human body that supports filtering excess water and waste from the blood. Kidney diseases generally occur due to changes in certain supplements, medical conditions, obesity, and diet, which causes kidney functi...

Enhanced IDOL segmentation framework using personalized hyperspace learning IDOL.

Medical physics
BACKGROUND: Adaptive radiotherapy (ART) workflows have been increasingly adopted to achieve dose escalation and tissue sparing under shifting anatomic conditions, but the necessity of recontouring and the associated time burden hinders a real-time or...

Diagnostic accuracy of chest X-ray and CT using artificial intelligence for osteoporosis: systematic review and meta-analysis.

Journal of bone and mineral metabolism
INTRODUCTION: Artificial intelligence (AI)-based systems using chest images are potentially reliable for diagnosing osteoporosis.

Fast prediction of personalized abdominal organ doses from CT examinations by radiomics feature-based machine learning models.

Scientific reports
The X-rays emitted during CT scans can increase solid cancer risks by damaging DNA, with the risk tied to patient-specific organ doses. This study aims to establish a new method to predict patient specific abdominal organ doses from CT examinations u...

Predicting the risk category of thymoma with machine learning-based computed tomography radiomics signatures and their between-imaging phase differences.

Scientific reports
The aim of this study was to develop a medical imaging and comprehensive stacked learning-based method for predicting high- and low-risk thymoma. A total of 126 patients with thymomas and 5 patients with thymic carcinoma treated at our institution, i...

FA-Net: A hierarchical feature fusion and interactive attention-based network for dose prediction in liver cancer patients.

Artificial intelligence in medicine
Dose prediction is a crucial step in automated radiotherapy planning for liver cancer. Several deep learning-based approaches for dose prediction have been proposed to enhance the design efficiency and quality of radiotherapy plan. However, these app...

Prediction of CD8+T lymphocyte infiltration levels in gastric cancer from contrast-enhanced CT and clinical factors using machine learning.

Medical physics
BACKGROUND: CD8+ T lymphocyte infiltration is closely associated with the prognosis and immunotherapy response of gastric cancer (GC). For now, the examination of CD8 infiltration levels relies on endoscopic biopsy, which is invasive and unsuitable f...

Machine learning models can define clinically relevant bone density subgroups based on patient-specific calibrated computed tomography scans in patients undergoing reverse shoulder arthroplasty.

Journal of shoulder and elbow surgery
BACKGROUND: Reduced bone density is recognized as a predictor for potential complications in reverse shoulder arthroplasty (RSA). While humeral and glenoid planning based on preoperative computed tomography (CT) scans assist in implant selection and ...