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As Breast Cancer Awareness Month wraps up, pink ribbons, public campaigns, and powerful personal stories remind us of one crucial truth: early detection saves lives. Finding breast cancer early can mean simpler treatment and a far better chance of survival.
Breast cancer doesn’t behave the same way in every woman, and it certainly doesn’t behave the same way across borders. From access to screening technology to the age and frequency of recommended mammograms, there’s no one-size-fits-all approach.
Can artificial intelligence (AI) help make breast cancer screening smarter, more personal, and potentially more effective – provided it remains guided by human judgment?
From One-Size-Fits-All to Personalized Screening
Guidelines around the world vary. In the U.S., the American College of Radiology recommends yearly mammograms from age 40, while the U.S. Preventive Services Task Force suggests screening every two years from 40 to 74. In Europe, countries like Sweden and the UK invite women aged 50–69 for mammograms every 2–3 years through national programs.
In many low- and middle-income countries, regular screening is limited or unavailable, leading to later diagnoses. Differences reflect healthcare budgets, infrastructure, and public awareness, and highlight the challenge of balancing early detection with the risk of over-diagnosis.
AI offers a potential bridge. By analyzing millions of mammograms and patient histories, it can spot patterns invisible to the human eye and estimate a woman’s risk more precisely.
What the Science Shows
In a Swedish study, known as the MASAI trial and published in The Lancet, researchers compared standard mammogram readings with AI-assisted screening. The results showed that AI-supported reading detected 29% more cancers, including smaller, early-stage tumors that are often easier to treat. It achieved this without significantly increasing false positives, and it cut radiologists’ workload nearly in half.
Another study in the Netherlands, also published in the Lancet, evaluated over 42,000 mammograms and found that combining AI with a single human reader was more sensitive than standard double reading. (Editor’s note: mammograms and other types of screening are usually read and interpreted by two radiologists.)
AI can flag suspicious areas on mammograms, helping doctors reach diagnoses faster and ensuring images are high quality, reducing the need for repeat scans.
For health systems with limited resources or a shortage of radiologists, that efficiency is a game-changer. Yet, the study’s lead investigators emphasized a critical point: AI didn’t replace doctors; it worked alongside them, flagging areas of concern while leaving final decisions to radiologists.
The Lebanese Picture: Awareness, Access, and Adaptation
In Lebanon, breast cancer remains the most common cancer among women, representing more than 38% of all female cancer cases. National awareness campaigns launched by the Ministry of Public Health since 2002 have encouraged women over 40 to get yearly mammograms, often offered at reduced or no cost, improving early detection and survival rates.
Still, challenges persist: from unequal access between urban centers and rural areas to differences in how screening guidelines are applied.
Dr. Tamina Elias-Rizk, Chief of Section of Breast Imaging at the Lebanese American University SOM-LAUMC, explains that individualized screening, rather than national screening, remains essential.
“We do a risk assessment at age 25,” she says. “Starting at 40, we recommend yearly mammograms and ultrasounds. For women with dense breasts, where glandular tissue makes it harder to see tumors, we advise an MRI every two to three years.”
When Risk Runs in the Family
Family history also shapes screening plans. “If a woman’s mother had breast cancer at 42, we start her screening at 32,” Dr. Elias-Rizk explains. “Before 35, we rely on ultrasound and MRI; after 35, we add mammography.”
Such personalized schedules underscore how medicine is moving away from rigid rules toward risk-based approaches, something AI could enhance. By analyzing thousands of cases, AI can help classify patients into higher- or lower-risk groups, suggesting who may need closer monitoring.
Dr Elias-Rizk also notes, “The risk assessment is not only done at the level of the radiologist but also at dispensaries, family doctors, and gynecologists.”
Can AI Help in Lebanon?
In Lebanon, where screening participation rates fluctuate, and radiologist distribution is uneven, AI could play a complementary role. “When we run national campaigns and don’t have enough radiologists to read every scan, AI can help triage – highlighting which cases to prioritize,” says Dr. Elias-Rizk.
Dr. Mary Chammas, Chairwoman of Obstetrics and Gynecology at Saint George Hospital, acknowledges that AI-assisted systems can aid early detection but says genetic screening still offers powerful guidance.
“AI can help in detection,” she explains. “However, genetic screening can help triage women into high and low risk and adapt their screening protocol.”
The Promise – and the Limits – of AI
AI models can sometimes predict breast cancer risk years in advance by detecting subtle mammogram patterns.
However, experts caution against overreliance. Algorithms are only as good as the data they are trained on. Most models are based on Western populations, which may not reflect Lebanese women, who often develop cancer earlier and have denser breasts.
There’s also the question of accountability. As Dr. Elias-Rizk notes, “If a lesion appears stable and later turns out to be cancerous, who is responsible: the AI system or the radiologist?”
Until we can answer that, AI should remain a tool, not a decision-maker.
The Human Connection Remains Central
Still, optimism remains. “AI is improving,” Elias-Rizk says. “Digital mammography improved imaging for dense breasts; AI will also advance. But medicine will always rely on human judgment and compassion.”
While the debate around AI continues, doctors agree on one point: screening, by any means, saves lives. In Lebanon and worldwide, many women delay or skip mammograms due to fear, access, or misconceptions. Even the best technology is only effective if women participate.
As AI continues to evolve, its greatest impact may be in empowering doctors, not replacing them. By automating repetitive tasks, highlighting subtle findings, and identifying women at highest risk, AI can help specialists spend more time on what truly matters: interpreting results, explaining options, and guiding care.
As one post read on social media during Breast Cancer Awareness Month put it: “The only pink thing about breast cancer is the ribbon that represents it.”
Get screened! So if breast cancer does appear, you have the best chance to beat it.
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