AIMC Topic: Neoplasm Metastasis

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Identifying metastatic ability of prostate cancer cell lines using native fluorescence spectroscopy and machine learning methods.

Scientific reports Jan 26, 2021
Metastasis is the leading cause of mortalities in cancer patients due to the spreading of cancer cells to various organs. Detecting cancer and identifying its metastatic potential at the early stage is important. This may be achieved based on the qua...
NAD Prostatic Neoplasms Neoplasm Metastasis Lactic Acid Machine Learning Tryptophan Reproducibility of Results Male Cell Line, Tumor ROC Curve Support Vector Machine Principal Component Analysis Spectrometry, Fluorescence Humans
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Machine-Learning Provides Patient-Specific Prediction of Metastatic Risk Based on Innovative, Mechanobiology Assay.

Annals of biomedical engineering Jan 22, 2021
Cancer mortality is mostly related to metastasis. Metastasis is currently prognosed via histopathology, disease-statistics, or genetics; those are potentially inaccurate, not rapidly available and require known markers. We had developed a rapid (~ 2 ...
Humans Machine Learning Female Predictive Value of Tests Models, Biological Neoplasm Metastasis Male Biophysics Neoplasms Cell Line, Tumor Cell Movement
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Small Steatotic HCC: A Radiological Variant Associated With Improved Outcome After Ablation.

Hepatology communications Dec 31, 2020
Percutaneous thermal ablation is a validated treatment option for small hepatocellular carcinoma (HCC). Steatotic HCC can be reliably detected by magnetic resonance imaging. To determine the clinical relevance of this radiological variant, we include...
Treatment Outcome Follow-Up Studies Male Magnetic Resonance Imaging Humans Disease-Free Survival Neoplasm Recurrence, Local Middle Aged Retrospective Studies Catheter Ablation Liver Neoplasms Female Neoplasm Metastasis Carcinoma, Hepatocellular Aged
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CUP-AI-Dx: A tool for inferring cancer tissue of origin and molecular subtype using RNA gene-expression data and artificial intelligence.

EBioMedicine Oct 9, 2020
BACKGROUND: Cancer of unknown primary (CUP), representing approximately 3-5% of all malignancies, is defined as metastatic cancer where a primary site of origin cannot be found despite a standard diagnostic workup. Because knowledge of a patient's pr...
Software Algorithms Reproducibility of Results Biomarkers, Tumor Humans Neural Networks, Computer Artificial Intelligence Machine Learning RNA Neoplasm Metastasis Neoplasms, Unknown Primary Genomics Computational Biology Databases, Genetic Workflow
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Robust edge-based biomarker discovery improves prediction of breast cancer metastasis.

BMC bioinformatics Sep 30, 2020
BACKGROUND: The abundance of molecular profiling of breast cancer tissues entailed active research on molecular marker-based early diagnosis of metastasis. Recently there is a surging interest in combining gene expression with gene networks such as p...
Logistic Models Support Vector Machine Area Under Curve Neoplasm Metastasis Biomarkers, Tumor ROC Curve Protein Interaction Maps Gene Regulatory Networks Humans Female Breast Neoplasms
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Serum markers improve current prediction of metastasis development in early-stage melanoma patients: a machine learning-based study.

Molecular oncology Jun 24, 2020
Metastasis development represents an important threat for melanoma patients, even when diagnosed at early stages and upon removal of the primary tumor. In this scenario, determination of prognostic biomarkers would be of great interest. Serum contain...
Middle Aged Peptides ROC Curve Neoplasm Staging Neoplasm Metastasis Female Melanoma Biomarkers, Tumor Male Humans Machine Learning Cytokines Prognosis
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Development and validation of a deep learning system for ascites cytopathology interpretation.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association Jun 4, 2020
BACKGROUND: Early diagnosis of Peritoneal metastasis (PM) is clinically significant regarding optimal treatment selection and avoidance of unnecessary surgical procedures. Cytopathology plays an important role in early screening of PM. We aimed to de...
Deep Learning Early Detection of Cancer Area Under Curve Ascites Peritoneal Neoplasms Image Interpretation, Computer-Assisted Neoplasm Metastasis Humans Datasets as Topic Neural Networks, Computer Reproducibility of Results
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Prediction of breast cancer proteins involved in immunotherapy, metastasis, and RNA-binding using molecular descriptors and artificial neural networks.

Scientific reports May 22, 2020
Breast cancer (BC) is a heterogeneous disease where genomic alterations, protein expression deregulation, signaling pathway alterations, hormone disruption, ethnicity and environmental determinants are involved. Due to the complexity of BC, the predi...
Humans Neural Networks, Computer Machine Learning Female Breast Neoplasms Biomarkers, Tumor Neoplasm Metastasis Gene Expression Profiling Immunotherapy Gene Expression Regulation, Neoplastic RNA
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Convolutional Neural Networks in Predicting Nodal and Distant Metastatic Potential of Newly Diagnosed Non-Small Cell Lung Cancer on FDG PET Images.

AJR. American journal of roentgenology Apr 29, 2020
The purpose of this study was to assess, by analyzing features of the primary tumor with F-FDG PET, the utility of deep machine learning with a convolutional neural network (CNN) in predicting the potential of newly diagnosed non-small cell lung can...
Neoplasm Metastasis Fluorodeoxyglucose F18 Humans Lymphatic Metastasis Aged, 80 and over Predictive Value of Tests Middle Aged Neural Networks, Computer Adult Positron Emission Tomography Computed Tomography Imaging, Three-Dimensional Retrospective Studies Sensitivity and Specificity Radiopharmaceuticals Lung Neoplasms Female Male Carcinoma, Non-Small-Cell Lung Aged
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Machine Learning Analysis of Individual Tumor Lesions in Four Metastatic Colorectal Cancer Clinical Studies: Linking Tumor Heterogeneity to Overall Survival.

The AAPS journal Mar 16, 2020
Total tumor size (TS) metrics used in TS models in oncology do not consider tumor heterogeneity, which could help to better predict drug efficacy. We analyzed individual target lesions (iTLs) of patients with metastatic colorectal carcinoma (mCRC) to...
Clinical Studies as Topic Neoplasm Metastasis Proportional Hazards Models Machine Learning Colorectal Neoplasms Antineoplastic Agents Humans Carcinoma
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