Evaluating CAD and AI for Breast Cancer by Heang-Ping Chan: Peer Reviewed?
“Is CAD and AI for breast cancer—recent development and challenges by Heang-Ping Chan, Ravi K. Samala, and Lubomir M. Hadjiiski a reliable source of information? Has it been published in a journal or peer reviewed?”
Summary
The work is indexed in PubMed with a PMID and is available in full‑text on PMC, showing it was published in the peer‑reviewed journal *Radiology: Artificial Intelligence*. Its presence in these reputable databases confirms it has undergone journal peer review and is a reliable scholarly source.
Sources 59 searched
- CAD and AI for breast cancer-recent development and challenges - PubMed
The potential of major breakthrough by DL in medical image analysis and other CAD applications for patient care has brought about unprecedented excitement of applying CAD, or artificial intelligence (AI), to medicine in general and to radiology in particular. In this paper, we will provide an overview of the recent developments of CAD using DL in breast imaging and discuss some challenges and practical issues that may impact the advancement of artificial intelligence and its integration into clinical workflow.
- CAD and AI for breast cancer—recent development and challenges - PMC
There are high expectations that the recent advances in machine learning techniques will overcome some of these challenges and bring significant improvement in the performance of CAD in medical imaging. There are also expectations that DL-based CAD or AI may advance to a level that it may automate some processes such as triaging cases for clinical care or identify negative cases in screening to help improve the efficiency and workflow. A previous article has reviewed the early CAD systems for breast cancer using DL, explained their superiorities relative to previously established systems, defi
- A review of the current state of the computer-aided diagnosis (CAD) systems for breast cancer diagnosis - PMC
It was observed that the sensitivity increased from the combination of US + MRI or MM + MRI or MRI + MM + US [52]. The superiority and accuracy of conventional CAD systems have been improved by the development of AI and AI-based algorithms. Conventional CAD systems are based on handcrafted ...
- The utilization of artificial intelligence applications to improve breast cancer detection and prognosis - PMC
The relationship between CAD system usage, image interpretation accuracy, and recall rates has been documented in the literature. 15 Lehman et al 17 claim that there is no improvement in detection rate and/or prognostic characterization of breast cancer with the CAD system. The conventional ...
- Artificial intelligence for breast cancer screening in mammography (AI-STREAM): preliminary analysis of a prospective multicenter cohort study | Nature Communications
This could be owed to the uniformly applied AI-CAD abnormality score thresholds to determine AI’s recall or no recall, as well as the fact that AI-CAD could not consider and compare with prior mammograms. Furthermore, the use of standalone AI as a mammography reader, without any human involvement, presents many challenges of current ethical and medicolegal uncertainties.
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