AIMC Topic: Neoplasm Metastasis
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Machine learning of genomic features in organotropic metastases stratifies progression risk of primary tumors.
Nature communications
Nov 18, 2021
Metastatic cancer is associated with poor patient prognosis but its spatiotemporal behavior remains unpredictable at early stage. Here we develop MetaNet, a computational framework that integrates clinical and sequencing data from 32,176 primary and ...
Cell-morphodynamic phenotype classification with application to cancer metastasis using cell magnetorotation and machine-learning.
PloS one
Nov 17, 2021
We define cell morphodynamics as the cell's time dependent morphology. It could be called the cell's shape shifting ability. To measure it we use a biomarker free, dynamic histology method, which is based on multiplexed Cell Magneto-Rotation and Mach...
Dynamic Learning Rate in Deep CNN Model for Metastasis Detection and Classification of Histopathology Images.
Computational and mathematical methods in medicine
Oct 26, 2021
Diagnosis of different breast cancer stages using histopathology whole slide images (WSI) is the gold standard in determining the grade of tissue metastasis. Computer-aided diagnosis (CAD) assists medical experts as a second opinion tool in early det...
A new prognostic score for predicting survival in patients treated with robotic stereotactic radiotherapy for brain metastases.
Scientific reports
Oct 13, 2021
The study aimed to analyze potential prognostic factors in patients treated with robotic radiosurgery for brain metastases irrespective of primary tumor location and create a simple prognostic score that can be used without a full diagnostic workup. ...
Few-Shot Breast Cancer Metastases Classification via Unsupervised Cell Ranking.
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
Tumor metastases detection is of great importance for the treatment of breast cancer patients. Various CNN (convolutional neural network) based methods get excellent performance in object detection/segmentation. However, the detection of metastases i...
Patterns of Metastatic Disease in Patients with Cancer Derived from Natural Language Processing of Structured CT Radiology Reports over a 10-year Period.
Radiology
Aug 3, 2021
Background Patterns of metastasis in cancer are increasingly relevant to prognostication and treatment planning but have historically been documented by means of autopsy series. Purpose To show the feasibility of using natural language processing (NL...
Machine learning reveals mesenchymal breast carcinoma cell adaptation in response to matrix stiffness.
PLoS computational biology
Jul 23, 2021
Epithelial-mesenchymal transition (EMT) and its reverse process, mesenchymal-epithelial transition (MET), are believed to play key roles in facilitating the metastatic cascade. Metastatic lesions often exhibit a similar epithelial-like state to that ...
Humans
Cell Proliferation
Cell Shape
Biomarkers, Tumor
Extracellular Matrix
Antigens, CD
Biophysical Phenomena
Adaptation, Physiological
Cell Line, Tumor
Cell Count
Cell Adhesion
Computational Biology
Epithelial-Mesenchymal Transition
Machine Learning
Triple Negative Breast Neoplasms
Cadherins
Female
Models, Biological
Tumor Microenvironment
Vimentin
Neoplasm Metastasis
Role of Regulatory Non-Coding RNAs in Aggressive Thyroid Cancer: Prospective Applications of Neural Network Analysis.
Molecules (Basel, Switzerland)
May 19, 2021
Thyroid cancer (TC) is the most common endocrine malignancy. Most TCs have a favorable prognosis, whereas anaplastic thyroid carcinoma (ATC) is a lethal form of cancer. Different genetic and epigenetic alterations have been identified in aggressive f...
EARN: an ensemble machine learning algorithm to predict driver genes in metastatic breast cancer.
BMC medical genomics
May 7, 2021
BACKGROUND: Today, there are a lot of markers on the prognosis and diagnosis of complex diseases such as primary breast cancer. However, our understanding of the drivers that influence cancer aggression is limited.
AI-based pathology predicts origins for cancers of unknown primary.
Nature
May 5, 2021
Cancer of unknown primary (CUP) origin is an enigmatic group of diagnoses in which the primary anatomical site of tumour origin cannot be determined. This poses a considerable challenge, as modern therapeutics are predominantly specific to the primar...
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