AI Medical Compendium Topic:
Biomarkers, Tumor

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Ultrasensitive flexible FET-type aptasensor for CA 125 cancer marker detection based on carboxylated multiwalled carbon nanotubes immobilized onto reduced graphene oxide film.

Analytica chimica acta
The development of a novel flexible and ultrasensitive aptasensor based on carboxylated multiwalled carbon nanotubes (MWCNTs)/ reduced graphene oxide-based field effect transistor (FET) has been reported for label-free detection of the ovarian cancer...

A novel algorithm to improve specificity in ovarian cancer detection.

Cancer treatment and research communications
BACKGROUND: Measurement of autoantibodies (AAbs) to tumor associated antigens has been proposed to aid in the early detection of ovarian cancer with high specificity. Here we describe a multiplex approach to evaluate selected peptide epitopes of p53 ...

Digital image analysis in breast pathology-from image processing techniques to artificial intelligence.

Translational research : the journal of laboratory and clinical medicine
Breast cancer is the most common malignant disease in women worldwide. In recent decades, earlier diagnosis and better adjuvant therapy have substantially improved patient outcome. Diagnosis by histopathology has proven to be instrumental to guide br...

An Improved Binary Differential Evolution Algorithm for Feature Selection in Molecular Signatures.

Molecular informatics
The discovery of biomarkers from high-dimensional data is a very challenging task in cancer diagnoses. On the one hand, biomarker discovery is the so-called high-dimensional small-sample problem. On the other hand, these data are redundant and noisy....

Interactive phenotyping of large-scale histology imaging data with HistomicsML.

Scientific reports
Whole-slide imaging of histologic sections captures tissue microenvironments and cytologic details in expansive high-resolution images. These images can be mined to extract quantitative features that describe tissues, yielding measurements for hundre...

A novel machine learning approach reveals latent vascular phenotypes predictive of renal cancer outcome.

Scientific reports
Gene expression signatures are commonly used as predictive biomarkers, but do not capture structural features within the tissue architecture. Here we apply a 2-step machine learning framework for quantitative imaging of tumor vasculature to derive a ...

Deep Learning-Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer.

Clinical cancer research : an official journal of the American Association for Cancer Research
Identifying robust survival subgroups of hepatocellular carcinoma (HCC) will significantly improve patient care. Currently, endeavor of integrating multi-omics data to explicitly predict HCC survival from multiple patient cohorts is lacking. To fill ...

Serum levels of chemical elements in esophageal squamous cell carcinoma in Anyang, China: a case-control study based on machine learning methods.

BMJ open
OBJECTIVES: Esophageal squamous cell carcinoma (ESCC) is the predominant form of esophageal carcinoma with extremely aggressive nature and low survival rate. The risk factors for ESCC in the high-incidence areas of China remain unclear. We used machi...

A hierarchical classifier based on human blood plasma fluorescence for non-invasive colorectal cancer screening.

Artificial intelligence in medicine
Colorectal cancer (CRC) a leading cause of death by cancer, and screening programs for its early identification are at the heart of the increasing survival rates. To motivate population participation, non-invasive, accurate, scalable and cost-effecti...

Prostate-Specific Membrane Antigen Positron Emission Tomography-Computed Tomography for Prostate Cancer: Distribution of Disease and Implications for Radiation Therapy Planning.

International journal of radiation oncology, biology, physics
PURPOSE: To explore the prostate-specific membrane antigen (PSMA)-avid distribution of prostate cancer (PC) on positron emission tomography (PET), both at the time of initial diagnosis and at the time of relapse after definitive local treatment.