AIMC Topic: Early Detection of Cancer

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Evaluation of deep learning methods for early gastric cancer detection using gastroscopic images.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: A timely diagnosis of early gastric cancer (EGC) can greatly reduce the death rate of patients. However, the manual detection of EGC is a costly and low-accuracy task. The artificial intelligence (AI) method based on deep learning is cons...

New Horizons: Artificial Intelligence for Digital Breast Tomosynthesis.

Radiographics : a review publication of the Radiological Society of North America, Inc
The use of digital breast tomosynthesis (DBT) in breast cancer screening has become widely accepted, facilitating increased cancer detection and lower recall rates compared with those achieved by using full-field digital mammography (DM). However, th...

A deep learning-based method for cervical transformation zone classification in colposcopy images.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Colposcopy is one of the common methods of cervical cancer screening. The type of cervical transformation zone is considered one of the important factors for grading colposcopic findings and choosing treatment.

Past, Present, and Future of Machine Learning and Artificial Intelligence for Breast Cancer Screening.

Journal of breast imaging
Breast cancer screening has evolved substantially over the past few decades because of advancements in new image acquisition systems and novel artificial intelligence (AI) algorithms. This review provides a brief overview of the history, current stat...

Deep Learning vs Traditional Breast Cancer Risk Models to Support Risk-Based Mammography Screening.

Journal of the National Cancer Institute
BACKGROUND: Deep learning breast cancer risk models demonstrate improved accuracy compared with traditional risk models but have not been prospectively tested. We compared the accuracy of a deep learning risk score derived from the patient's prior ma...

Deep Learning Empowers Lung Cancer Screening Based on Mobile Low-Dose Computed Tomography in Resource-Constrained Sites.

Frontiers in bioscience (Landmark edition)
BACKGROUND: Existing challenges of lung cancer screening included non-accessibility of computed tomography (CT) scanners and inter-reader variability, especially in resource-limited areas. The combination of mobile CT and deep learning technique has ...

Natural Language Processing to Identify Abnormal Breast, Lung, and Cervical Cancer Screening Test Results from Unstructured Reports to Support Timely Follow-up.

Studies in health technology and informatics
Cancer screening and timely follow-up of abnormal results can reduce mortality. One barrier to follow-up is the failure to identify abnormal results. While EHRs have coded results for certain tests, cancer screening results are often stored in free-t...

Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings: a systematic review.

The Lancet. Digital health
Skin cancers occur commonly worldwide. The prognosis and disease burden are highly dependent on the cancer type and disease stage at diagnosis. We systematically reviewed studies on artificial intelligence and machine learning (AI/ML) algorithms that...