AIMC Topic: Neoplasm Invasiveness

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Ultrasound-based deep learning radiomics in the assessment of pathological complete response to neoadjuvant chemotherapy in locally advanced breast cancer.

European journal of cancer (Oxford, England : 1990) Feb 24, 2021
PURPOSE: The aim of the study was to develop and validate a deep learning radiomic nomogram (DLRN) for preoperatively assessing breast cancer pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) based on the pre- and post-treatme...
Humans Female Retrospective Studies Reproducibility of Results Clinical Decision-Making Adult Breast Neoplasms Middle Aged Neoplasm Invasiveness Predictive Value of Tests Ultrasonography, Mammary Mastectomy Image Interpretation, Computer-Assisted Deep Learning Nomograms Treatment Outcome Neoadjuvant Therapy Observer Variation Chemotherapy, Adjuvant
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Deep learning-based differentiation of invasive adenocarcinomas from preinvasive or minimally invasive lesions among pulmonary subsolid nodules.

European radiology Feb 8, 2021
OBJECTIVES: To evaluate a deep learning-based model using model-generated segmentation masks to differentiate invasive pulmonary adenocarcinoma (IPA) from preinvasive lesions or minimally invasive adenocarcinoma (MIA) on CT, making comparisons with r...
Deep Learning Lung Neoplasms Adenocarcinoma Neoplasm Invasiveness Diagnosis, Differential Humans Retrospective Studies Tomography, X-Ray Computed
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A Machine Learning Approach Yields a Multiparameter Prognostic Marker in Liver Cancer.

Cancer immunology research Jan 11, 2021
A number of staging systems have been developed to predict clinical outcomes in hepatocellular carcinoma (HCC). However, no general consensus has been reached regarding the optimal model. New approaches such as machine learning (ML) strategies are po...
Machine Learning Prognosis Retrospective Studies Female Risk Factors Humans Middle Aged Risk Assessment Adolescent Liver Neoplasms Carcinoma, Hepatocellular Young Adult Adult T-Lymphocytes Male Immune Checkpoint Proteins Hepatectomy Portal Vein Lymphocyte Count Kaplan-Meier Estimate Models, Immunological Venous Thrombosis Neoplasm Invasiveness Liver Neoplasm Staging
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3D deep learning based classification of pulmonary ground glass opacity nodules with automatic segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Dec 11, 2020
Classifying ground-glass lung nodules (GGNs) into atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) on diagnostic CT images is important to evaluate the th...
Lung Neoplasms Adenocarcinoma Neoplasm Invasiveness Humans Retrospective Studies Tomography, X-Ray Computed Deep Learning
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Thin-Slice Pituitary MRI with Deep Learning-based Reconstruction: Diagnostic Performance in a Postoperative Setting.

Radiology Nov 3, 2020
Background Achieving high-spatial-resolution pituitary MRI is challenging because of the trade-off between image noise and spatial resolution. Deep learning-based MRI reconstruction enables image denoising with sharp edges and reduced artifacts, whic...
Pituitary Neoplasms Adenoma Postoperative Care Image Interpretation, Computer-Assisted Pituitary Gland Male Middle Aged Deep Learning Magnetic Resonance Imaging Neoplasm Invasiveness Humans Female
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Machine learning to predict the cancer-specific mortality of patients with primary non-metastatic invasive breast cancer.

Surgery today Oct 26, 2020
PURPOSE: We used five machine-learning algorithms to predict cancer-specific mortality after surgical resection of primary non-metastatic invasive breast cancer.
Humans Machine Learning Prognosis Female Survival Rate Breast Neoplasms Mastectomy Logistic Models Neoplasm Invasiveness
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Volumetric breast density estimation on MRI using explainable deep learning regression.

Scientific reports Oct 22, 2020
To purpose of this paper was to assess the feasibility of volumetric breast density estimations on MRI without segmentations accompanied with an explainability step. A total of 615 patients with breast cancer were included for volumetric breast densi...
Breast Density Carcinoma, Lobular Adult Breast Neoplasms Middle Aged Deep Learning Image Processing, Computer-Assisted Follow-Up Studies Magnetic Resonance Imaging Neoplasm Invasiveness Carcinoma, Ductal, Breast Prospective Studies Prognosis Female Aged Aged, 80 and over Humans Neural Networks, Computer Algorithms
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Using Deep Learning with Convolutional Neural Network Approach to Identify the Invasion Depth of Endometrial Cancer in Myometrium Using MR Images: A Pilot Study.

International journal of environmental research and public health Aug 18, 2020
Myometrial invasion affects the prognosis of endometrial cancer. However, discrepancies exist between pre-operative magnetic resonance imaging staging and post-operative pathological staging. This study aims to validate the accuracy of artificial int...
Neoplasm Staging Endometrial Neoplasms Myometrium Sensitivity and Specificity Deep Learning Pilot Projects Magnetic Resonance Imaging Humans Neoplasm Invasiveness Neural Networks, Computer Artificial Intelligence Female
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Artificial intelligence-assisted cytology for detection of cervical intraepithelial neoplasia or invasive cancer: A multicenter, clinical-based, observational study.

Gynecologic oncology Aug 16, 2020
OBJECTIVE: Artificial intelligence (AI) could automatedly detect abnormalities in digital cytological images, however, the effect in cervical cancer screening is inconclusive. We aim to evaluate the performance of AI-assisted cytology for the detecti...
Cervix Uteri Early Detection of Cancer Neoplasm Invasiveness Predictive Value of Tests Triage Deep Learning Image Processing, Computer-Assisted Vaginal Smears Papillomavirus Infections Colposcopy Humans Biopsy Female Datasets as Topic Adult Uterine Cervical Dysplasia Uterine Cervical Neoplasms Papillomaviridae Middle Aged Severity of Illness Index
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Real-time assessment of video images for esophageal squamous cell carcinoma invasion depth using artificial intelligence.

Journal of gastroenterology Aug 10, 2020
BACKGROUND: Although optimal treatment of superficial esophageal squamous cell carcinoma (SCC) requires accurate evaluation of cancer invasion depth, the current process is rather subjective and may vary by observer. We, therefore, aimed to develop a...
Esophagoscopy Humans Neural Networks, Computer Artificial Intelligence Retrospective Studies Middle Aged Neoplasm Invasiveness Esophageal Neoplasms Esophageal Squamous Cell Carcinoma Narrow Band Imaging Female Aged Sensitivity and Specificity Male
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