AI Medical Compendium Topic:
Biomarkers, Tumor

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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.

An Advanced Deep Learning Approach for Ki-67 Stained Hotspot Detection and Proliferation Rate Scoring for Prognostic Evaluation of Breast Cancer.

Scientific reports
Being a non-histone protein, Ki-67 is one of the essential biomarkers for the immunohistochemical assessment of proliferation rate in breast cancer screening and grading. The Ki-67 signature is always sensitive to radiotherapy and chemotherapy. Due t...

Relevance of deep learning to facilitate the diagnosis of HER2 status in breast cancer.

Scientific reports
Tissue biomarker scoring by pathologists is central to defining the appropriate therapy for patients with cancer. Yet, inter-pathologist variability in the interpretation of ambiguous cases can affect diagnostic accuracy. Modern artificial intelligen...

MRF-ANN: a machine learning approach for automated ER scoring of breast cancer immunohistochemical images.

Journal of microscopy
Molecular pathology, especially immunohistochemistry, plays an important role in evaluating hormone receptor status along with diagnosis of breast cancer. Time-consumption and inter-/intraobserver variability are major hindrances for evaluating the r...

A deep learning based strategy for identifying and associating mitotic activity with gene expression derived risk categories in estrogen receptor positive breast cancers.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
The treatment and management of early stage estrogen receptor positive (ER+) breast cancer is hindered by the difficulty in identifying patients who require adjuvant chemotherapy in contrast to those that will respond to hormonal therapy. To distingu...

An Extended SNOMED CT Concept Model for Observations in Molecular Genetics.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Molecular genetics laboratory reports are multiplying and increasingly of clinical importance in diagnosis and treatment of cancer, infectious disease and managing of public health. Little of this data is structured or maintained in the EHR in format...

CyNetSVM: A Cytoscape App for Cancer Biomarker Identification Using Network Constrained Support Vector Machines.

PloS one
One of the important tasks in cancer research is to identify biomarkers and build classification models for clinical outcome prediction. In this paper, we develop a CyNetSVM software package, implemented in Java and integrated with Cytoscape as an ap...

Analysis of specific serum markers of colon carcinoma using a Bhattacharyya-based support vector machine.

Genetics and molecular research : GMR
We aimed to evaluate the specificity of 12 tumor markers related to colon carcinoma and identify the most sensitive index. Bhattacharyya distance was used to evaluate the index. Then, different index combinations were used to establish a support vect...