AIMC Topic: Tomography, X-Ray Computed

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Establishment and validation of multiclassification prediction models for pulmonary nodules based on machine learning.

The clinical respiratory journal
BACKGROUND: Lung cancer is the leading cause of cancer-related death worldwide. This study aimed to establish novel multiclassification prediction models based on machine learning (ML) to predict the probability of malignancy in pulmonary nodules (PN...

Deep-Learning Based Automated Segmentation and Quantitative Volumetric Analysis of Orbital Muscle and Fat for Diagnosis of Thyroid Eye Disease.

Investigative ophthalmology & visual science
PURPOSE: Thyroid eye disease (TED) is characterized by proliferation of orbital tissues and complicated by compressive optic neuropathy (CON). This study aims to utilize a deep-learning (DL)-based automated segmentation model to segment orbital muscl...

A Machine Learning Model to Predict the Histology of Retroperitoneal Lymph Node Dissection Specimens.

Anticancer research
BACKGROUND/AIM: While post-chemotherapy retroperitoneal lymph node dissection (PC-RPLND) benefits patients with teratoma or viable germ cell tumors (GCT), it becomes overtreatment if necrosis is detected in PC-RPLND specimens. Serum microRNA-371a-3p ...

Assistive AI in Lung Cancer Screening: A Retrospective Multinational Study in the United States and Japan.

Radiology. Artificial intelligence
Purpose To evaluate the impact of an artificial intelligence (AI) assistant for lung cancer screening on multinational clinical workflows. Materials and Methods An AI assistant for lung cancer screening was evaluated on two retrospective randomized m...

Deep Learning Classification of Usual Interstitial Pneumonia Predicts Outcomes.

American journal of respiratory and critical care medicine
Computed tomography (CT) enables noninvasive diagnosis of usual interstitial pneumonia (UIP), but enhanced image analyses are needed to overcome the limitations of visual assessment. Apply multiple instance learning (MIL) to develop an explainable ...

Adults Ischium Age Estimation Based on Deep Learning and 3D CT Reconstruction.

Fa yi xue za zhi
OBJECTIVES: To develop a deep learning model for automated age estimation based on 3D CT reconstructed images of Han population in western China, and evaluate its feasibility and reliability.

Age Estimation by Machine Learning and CT-Multiplanar Reformation of Cranial Sutures in Northern Chinese Han Adults.

Fa yi xue za zhi
OBJECTIVES: To establish age estimation models of northern Chinese Han adults using cranial suture images obtained by CT and multiplanar reformation (MPR), and to explore the applicability of cranial suture closure rule in age estimation of northern ...

[A survey on the application of convolutional neural networks in the diagnosis of occupational pneumoconiosis].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Pneumoconiosis ranks first among the newly-emerged occupational diseases reported annually in China, and imaging diagnosis is still one of the main clinical diagnostic methods. However, manual reading of films requires high level of doctors, and it i...

[Prediction of recurrence-free survival in lung adenocarcinoma based on self-supervised pre-training and multi-task learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Computed tomography (CT) imaging is a vital tool for the diagnosis and assessment of lung adenocarcinoma, and using CT images to predict the recurrence-free survival (RFS) of lung adenocarcinoma patients post-surgery is of paramount importance in tai...