AIMC Topic: Imaging Genomics
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Modality-Aware Discriminative Fusion Network for Integrated Analysis of Brain Imaging Genomics.
IEEE transactions on neural networks and learning systems
May 2, 2025
Mild cognitive impairment (MCI) represents an early stage of Alzheimer's disease (AD), characterized by subtle clinical symptoms that pose challenges for accurate diagnosis. The quest for the identification of MCI individuals has highlighted the impo...
Machine Learning-Based MRI Radiogenomics for Evaluation of Response to Induction Chemotherapy in Head and Neck Squamous Cell Carcinoma.
Academic radiology
Nov 18, 2023
RATIONALE AND OBJECTIVES: To develop and validate a radiogenomics model integrating clinical data, radiomics-based machine learning (RBML) classifiers, and transcriptomics data for predicting the response to induction chemotherapy (IC) in patients wi...
Radiogenomics and Artificial Intelligence Approaches Applied to Cardiac Computed Tomography Angiography and Cardiac Magnetic Resonance for Precision Medicine in Coronary Heart Disease: A Systematic Review.
Circulation. Cardiovascular imaging
Dec 17, 2021
The risk of coronary heart disease (CHD) clinical manifestations and patient management is estimated according to risk scores accounting multifactorial risk factors, thus failing to cover the individual cardiovascular risk. Technological improvements...
A radiogenomics application for prognostic profiling of endometrial cancer.
Communications biology
Dec 6, 2021
Prognostication is critical for accurate diagnosis and tailored treatment in endometrial cancer (EC). We employed radiogenomics to integrate preoperative magnetic resonance imaging (MRI, n = 487 patients) with histologic-, transcriptomic- and molecul...
Visual Analytics for Hypothesis-Driven Exploration in Computational Pathology.
IEEE transactions on visualization and computer graphics
Sep 1, 2021
Recent advances in computational and algorithmic power are evolving the field of medical imaging rapidly. In cancer research, many new directions are sought to characterize patients with additional imaging features derived from radiology and patholog...
Uncertainty quantification in the radiogenomics modeling of EGFR amplification in glioblastoma.
Scientific reports
Feb 16, 2021
Radiogenomics uses machine-learning (ML) to directly connect the morphologic and physiological appearance of tumors on clinical imaging with underlying genomic features. Despite extensive growth in the area of radiogenomics across many cancers, and i...
Automatic Prediction of MGMT Status in Glioblastoma via Deep Learning-Based MR Image Analysis.
BioMed research international
Sep 23, 2020
Methylation of the O-methylguanine methyltransferase (MGMT) gene promoter is correlated with the effectiveness of the current standard of care in glioblastoma patients. In this study, a deep learning pipeline is designed for automatic prediction of M...
Radiogenomics for predicting p53 status, PD-L1 expression, and prognosis with machine learning in pancreatic cancer.
British journal of cancer
Jul 21, 2020
BACKGROUND: Radiogenomics is an emerging field that integrates "Radiomics" and "Genomics". In the current study, we aimed to predict the genetic information of pancreatic tumours in a simple, inexpensive, and non-invasive manner, using cancer imaging...
Applications of radiomics and machine learning for radiotherapy of malignant brain tumors.
Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
May 11, 2020
BACKGROUND: Magnetic resonance imaging (MRI) and amino acid positron-emission tomography (PET) of the brain contain a vast amount of structural and functional information that can be analyzed by machine learning algorithms and radiomics for the use o...
Glioma
Magnetic Resonance Imaging
DNA Methylation
Diagnosis, Differential
Brain Neoplasms
Deep Learning
Promoter Regions, Genetic
Image Processing, Computer-Assisted
Isocitrate Dehydrogenase
Computational Biology
Imaging Genomics
Neoplasm Recurrence, Local
DNA Repair Enzymes
Progression-Free Survival
Tumor Suppressor Proteins
Positron-Emission Tomography
Neuroimaging
Radiotherapy Planning, Computer-Assisted
Radiosurgery
DNA Modification Methylases
Neoplasm Proteins
Glioblastoma
Radiation Oncology
Neoplasm Grading
Humans
Sensitivity and Specificity
Artificial intelligence radiogenomics for advancing precision and effectiveness in oncologic care (Review).
International journal of oncology
May 11, 2020
The new era of artificial intelligence (AI) has introduced revolutionary data‑driven analysis paradigms that have led to significant advancements in information processing techniques in the context of clinical decision‑support systems. These advances...
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