AIMC Topic: Image Interpretation, Computer-Assisted
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Deep learning-based analysis of EGFR mutation prevalence in lung adenocarcinoma H&E whole slide images.
The journal of pathology. Clinical research
Nov 1, 2024
EGFR mutations are a major prognostic factor in lung adenocarcinoma. However, current detection methods require sufficient samples and are costly. Deep learning is promising for mutation prediction in histopathological image analysis but has limitati...
[Applications of artificial intelligence for imaging-driven diagnosis and treatment of bone and soft tissue tumors].
Zhonghua zhong liu za zhi [Chinese journal of oncology]
Sep 23, 2024
Bone and soft tissue tumors occur in the musculoskeletal system, and malignant bone tumors of bone and soft tissue account for 0.2% of all human malignant tumors, and if not diagnosed and treated in a timely manner, patients may be at risk of a poor ...
Towards consistency in pediatric brain tumor measurements: Challenges, solutions, and the role of artificial intelligence-based segmentation.
Neuro-oncology
Sep 5, 2024
MR imaging is central to the assessment of tumor burden and changes over time in neuro-oncology. Several response assessment guidelines have been set forth by the Response Assessment in Pediatric Neuro-Oncology (RAPNO) working groups in different tum...
Comparative analysis of ChatGPT and Bard in answering pathology examination questions requiring image interpretation.
American journal of clinical pathology
Sep 3, 2024
OBJECTIVES: To evaluate the accuracy of ChatGPT and Bard in answering pathology examination questions requiring image interpretation.
Deep Learning Features Can Improve Radiomics-Based Prostate Cancer Aggressiveness Prediction.
JCO clinical cancer informatics
Sep 1, 2024
PURPOSE: Emerging evidence suggests that the use of artificial intelligence can assist in the timely detection and optimization of therapeutic approach in patients with prostate cancer. The conventional perspective on radiomics encompassing segmentat...
Combining AI and Radiomics to Improve the Accuracy of Breast US.
Radiology
Sep 1, 2024
A novel Skin lesion prediction and classification technique: ViT-GradCAM.
Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
Sep 1, 2024
BACKGROUND: Skin cancer is one of the highly occurring diseases in human life. Early detection and treatment are the prime and necessary points to reduce the malignancy of infections. Deep learning techniques are supplementary tools to assist clinica...
Deep Learning-based Unsupervised Domain Adaptation via a Unified Model for Prostate Lesion Detection Using Multisite Biparametric MRI Datasets.
Radiology. Artificial intelligence
Sep 1, 2024
Purpose To determine whether the unsupervised domain adaptation (UDA) method with generated images improves the performance of a supervised learning (SL) model for prostate cancer (PCa) detection using multisite biparametric (bp) MRI datasets. Materi...
Deep Learning Segmentation of Infiltrative and Enhancing Cellular Tumor at Pre- and Posttreatment Multishell Diffusion MRI of Glioblastoma.
Radiology. Artificial intelligence
Sep 1, 2024
Purpose To develop and validate a deep learning (DL) method to detect and segment enhancing and nonenhancing cellular tumor on pre- and posttreatment MRI scans in patients with glioblastoma and to predict overall survival (OS) and progression-free su...
Presurgical Upgrade Prediction of DCIS to Invasive Ductal Carcinoma Using Time-dependent Deep Learning Models with DCE MRI.
Radiology. Artificial intelligence
Sep 1, 2024
Purpose To determine whether time-dependent deep learning models can outperform single time point models in predicting preoperative upgrade of ductal carcinoma in situ (DCIS) to invasive malignancy at dynamic contrast-enhanced (DCE) breast MRI withou...
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