AIMC Topic: Early Detection of Cancer

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Hybrid Loss-Constrained Lightweight Convolutional Neural Networks for Cervical Cell Classification.

Sensors (Basel, Switzerland)
Artificial intelligence (AI) technologies have resulted in remarkable achievements and conferred massive benefits to computer-aided systems in medical imaging. However, the worldwide usage of AI-based automation-assisted cervical cancer screening sys...

The future of early cancer detection.

Nature medicine
A proactive approach to detecting cancer at an early stage can make treatments more effective, with fewer side effects and improved long-term survival. However, as detection methods become increasingly sensitive, it can be difficult to distinguish in...

Multi-Task Fusion for Improving Mammography Screening Data Classification.

IEEE transactions on medical imaging
Machine learning and deep learning methods have become essential for computer-assisted prediction in medicine, with a growing number of applications also in the field of mammography. Typically these algorithms are trained for a specific task, e.g., t...

Artificial Intelligence Evaluation of 122 969 Mammography Examinations from a Population-based Screening Program.

Radiology
Background Artificial intelligence (AI) has shown promising results for cancer detection with mammographic screening. However, evidence related to the use of AI in real screening settings remain sparse. Purpose To compare the performance of a commerc...

Development and validation of a deep learning model for detection of breast cancers in mammography from multi-institutional datasets.

PloS one
OBJECTIVES: The objective of this study was to develop and validate a state-of-the-art, deep learning (DL)-based model for detecting breast cancers on mammography.

Applications of Artificial Intelligence in Screening, Diagnosis, Treatment, and Prognosis of Colorectal Cancer.

Current oncology (Toronto, Ont.)
Colorectal cancer (CRC) is one of the most common cancers worldwide. Accurate early detection and diagnosis, comprehensive assessment of treatment response, and precise prediction of prognosis are essential to improve the patients' survival rate. In ...

A Study of Social and Behavioral Determinants of Health in Lung Cancer Patients Using Transformers-based Natural Language Processing Models.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Social and behavioral determinants of health (SBDoH) have important roles in shaping people's health. In clinical research studies, especially comparative effectiveness studies, failure to adjust for SBDoH factors will potentially cause confounding i...

Artificial intelligence in mammographic phenotyping of breast cancer risk: a narrative review.

Breast cancer research : BCR
BACKGROUND: Improved breast cancer risk assessment models are needed to enable personalized screening strategies that achieve better harm-to-benefit ratio based on earlier detection and better breast cancer outcomes than existing screening guidelines...