Artificial intelligence (AI) may help detect breast cancer earlier and more accurately than traditional methods alone. It may also help predict a person's risk of developing breast cancer.Health professionals use imaging scans like mammograms and breast ultrasounds to screen people for breast cancer, which can help with early detection. They may also assess a person's family history, genetics, and other factors to help determine their risk of developing the disease.Recent studies suggest that AI could help health professionals detect breast cancer more quickly and accurately than with traditional screening methods alone. The technology may also help predict a person's risk of breast cancer with greater precision. How does AI help with breast cancer detection?AI developers can train computer systems to recognize, interpret, and analyze patterns in data.For breast cancer detection, AI technicians input information gathered from large data sets of mammograms for the systems to learn from.The AI software uses the data to create an algorithm that outlines the characteristics of mammograms with and without cancer. The system can then compare new images to the algorithm to help identify abnormalities.How accurate is AI in detecting breast cancer?Research has found that AI could help detect breast cancer with similar or greater accuracy than radiologists alone.In a recent Swedish study, AI-supported screening detected cancer in 244 women after analyzing 39,996 mammograms. In a separate group, two radiologists each used traditional screening methods to analyze a different set of 40,024 mammograms, from which they were able to detect cancer in 203 women.The false positive rate was 1.5% in both groups, which means AI and radiologists both mistakenly detected breast cancer in 1.5% of the mammograms they analyzed.While the detection rates were similar between both groups, the AI screening method reduced the workload for radiologists and allowed them to spend 44% less time reading screens.A 2025 meta-analysis of eight studies indicated that AI techniques could detect breast cancer with better overall accuracy than radiologists.However, the researchers also highlighted the current limitations of AI screening. These included the technology sometimes failing to identify visible lesions or interpret ambiguous results like radiologists could.The researchers suggest that AI and traditional radiology combined may result in the most accurate and effective breast cancer detection.Researchers of a 2022 study agree that AI should support, rather than replace, radiologists. Their results indicate that a combination of AI and a radiologist could detect breast cancer 2.6% more accurately than a radiologist alone.Can AI detect early breast cancer?Early breast cancer detection and treatment can significantly improve a person's outlook for the disease. The survival rate is almost 100% for the earliest stages of breast cancer and declines to 22% at stage IV.Traditional screening mammograms miss about 20% of breast cancers, according to the National Cancer Institute.AI-supported screening may help reduce false-negative results and help identify breast cancer earlier, as research suggests it could improve overall screening accuracy. However, more research is necessary to understand the reliability and implications of the technology. »Learn more:How can people detect breast cancer early?Can AI assess individual breast cancer risk?Research suggests AI may be able to effectively assess a person's risk of developing breast cancer.Health professionals typically use tools like the Breast Cancer Risk Assessment tool (BCRAT) or the Breast Cancer Surveillance Consortium (BCSC) Risk Calculator to estimate a person's likelihood of developing the disease.The tools calculate an individual's risk based on several factors, including their age, race and ethnicity, and personal and family medical histories.A recent study found that AI may be able to predict a person's breast cancer risk without these factors.In the study, AI systems used mammogram images to predict people's risk of developing breast cancer more accurately than the BCSC risk model could.The researchers found that combining AI and the BCSC model achieved the most accurate results.Are there challenges in using AI for breast cancer detection?Potentially, AI offers significant developments in breast cancer detection. However, AI systems lack standardization and rigorous regulatory and ethical guidelines and may present several challenges for researchers and health professionals. These include:Research challenges: AI algorithms are not generalized and often include large numbers of variables. This may affect how consistently AI models are able to perform and the reliability of the data they provide. Scientists need more evidence from large-scale studies to assess how safe, accurate, and reliable the technology may be for breast cancer detection in real-world clinical settings.The 'black box enigma': Scientists may refer to AI algorithms as black boxes, as humans cannot always understand the patterns the models find and the decisions they make. This could lead to AI making incomprehensible mistakes that scientists cannot predict, detect, or understand.Ethical concerns: The use of AI raises various ethical issues, including contributing to health disparities and the effect on healthcare professionals that AI systems may replace.Economic challenges: AI algorithm and infrastructure development and maintenance involve substantial ongoing costs.Is a person's data secure when AI screens for breast cancer? There are complex legal, regulatory, and technological challenges that may affect a person's data security when AI is used for breast cancer screening. The Health Insurance Portability and Accountability Act (HIPAA) protects people's health information and health privacy rights in the United States. As a new and evolving technology, however, AI presents legal and regulatory challenges that may affect health data security.HIPAA may disclose 'de-identified' protected health information. This involves removing information that could identify an individual or link them to the data. However, researchers suggest AI healthcare may result in opportunities for re-identification, which could link sensitive and private information to specific individuals.Regulatory bodies, healthcare professionals, and AI developers may continue to determine and implement safety measures as the technology progresses.Can AI help reduce breast cancer disparities?Breast cancer disparities can prevent certain groups from receiving equitable screening and treatment. These disparities persist due to various factors, including racism, the underrepresentation of certain groups in clinical trials, and a lack of access to care.Breast cancer disparities affect Black women especially severely. The group has a 38% higher mortality rate than white women, despite having a lower incidence of the disease.Researchers suggest that AI is vulnerable to bias and may contribute to and exacerbate existing racial disparities in healthcare, such as breast cancer screening.Evidence suggests that AI reflects human bias as it learns from the data that people provide. Additionally, human choices may influence AI systems to perform in exploitative or discriminatory ways.AI may help to reduce racial disparities in breast cancer screening if the people who use the technology actively counter existing healthcare biases. This may involve the use of ethical AI programs and the inclusion of diverse data sets.SummaryResearchers tend to agree that AI breast cancer screening should be integrated to support, rather than replace, radiologists for the most accurate results.The technology may be a promising tool for breast cancer detection and risk prediction. However, it faces several challenges, including ethical concerns, excessive financial costs, and reliability issues.More research is needed to determine if the technology is safe, accurate, and reliable before it can be widely implemented.
9 minutes ago
