AI Medical Compendium Topic:
Early Detection of Cancer

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8-Hydroxy-2'-deoxyguanosine as a Discriminatory Biomarker for Early Detection of Breast Cancer.

Clinical breast cancer
BACKGROUND: Breast cancer (BC) is one of the most prevalent and reported cancers among Saudi women. Detection of BC in the early invasive stage (stages I, II) has an advantage in treating patients over detection in the late invasive stage (stages III...

CANDLE/Supervisor: a workflow framework for machine learning applied to cancer research.

BMC bioinformatics
BACKGROUND: Current multi-petaflop supercomputers are powerful systems, but present challenges when faced with problems requiring large machine learning workflows. Complex algorithms running at system scale, often with different patterns that require...

Application of data mining methods to improve screening for the risk of early gastric cancer.

BMC medical informatics and decision making
BACKGROUND: Although gastric cancer is a malignancy with high morbidity and mortality in China, the survival rate of patients with early gastric cancer (EGC) is high after surgical resection. To strengthen diagnosing and screening is the key to impro...

MRI Brain Tumour Segmentation Using Hybrid Clustering and Classification by Back Propagation Algorithm.

Asian Pacific journal of cancer prevention : APJCP
Generally the segmentation refers, the partitioning of an image into smaller regions to identify or locate the region of abnormality. Even though image segmentation is the challenging task in medical applications, due to contrary image, local observa...

Image Registration based Cervical Cancer Detection and Segmentation Using ANFIS Classifier.

Asian Pacific journal of cancer prevention : APJCP
Cervical cancer is the leading cancer in women around the world. In this paper, Adaptive Neuro Fuzzy Inference System (ANFIS) classifier based cervical cancer detection and segmentation methodology is proposed. This proposed system consists of the fo...

Automated detection of lung cancer at ultralow dose PET/CT by deep neural networks - Initial results.

Lung cancer (Amsterdam, Netherlands)
OBJECTIVES: We evaluated whether machine learning may be helpful for the detection of lung cancer in FDG-PET imaging in the setting of ultralow dose PET scans.

A collaborative computer aided diagnosis (C-CAD) system with eye-tracking, sparse attentional model, and deep learning.

Medical image analysis
Computer aided diagnosis (CAD) tools help radiologists to reduce diagnostic errors such as missing tumors and misdiagnosis. Vision researchers have been analyzing behaviors of radiologists during screening to understand how and why they miss tumors o...

Machine learning for diagnostic ultrasound of triple-negative breast cancer.

Breast cancer research and treatment
PURPOSE: Early diagnosis of triple-negative (TN) breast cancer is important due to its aggressive biological characteristics, poor clinical outcomes, and limited options for therapy. The goal of this study is to evaluate the potential of machine lear...

Deep Learning to Distinguish Recalled but Benign Mammography Images in Breast Cancer Screening.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: False positives in digital mammography screening lead to high recall rates, resulting in unnecessary medical procedures to patients and health care costs. This study aimed to investigate the revolutionary deep learning methods to distinguish...