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Advanced AI to Predict Breast Cancer | Arkangel AI

About 1 in 8 women will develop invasive breast cancer throughout their lifetime. Prevent it by identifying potential signs at an early stage.

Problem

Breast cancer remains a significant health concern as the most prominent cancer diagnosed in women, aside from non-melanoma skin cancers. Estimated figures for 2022 indicate that 281,360 cases of invasive breast cancer and an additional 48,930 in situ cases will emerge in the U.S., with a projected 43,240 fatalities (1). While typically more prevalent in women, breast cancer also affects men, with risk factors ranging from genetic predispositions and advanced age to lifestyle influences like obesity and alcohol consumption (2). Early detection is critical, with recommended screening techniques such as mammography and MRI pivotal in identifying cancer at treatable stages. Breast cancer's potential to metastasize heightens the urgency for prompt intervention, guided by a variety of treatments tailored to the stage and specifics of each case. With roughly 1 in 8 women (12%) developing invasive breast cancer in their lifetimes and 75% of diagnoses occurring post-55 years of age, it underscores the importance of ongoing research, effective treatment options, and comprehensive support systems for those affected (3)(4).

Why it matters

  • Breast cancer is the most common cancer in women, with an estimated 281,360 invasive cases and 48,930 in situ cases in the U.S. in 2022, and 43,240 projected deaths.
  • It affects both women and men, with risk factors including genetics, age, obesity, and alcohol consumption.
  • Early detection through mammography and MRI is vital, as 1 in 8 women will develop breast cancer in their lifetime, with 75% of cases occurring after age 55, emphasizing the need for research and effective treatment options.

Solution

“BreastAware”, an AI virtual assistant, emerges as a tool for doctors as it helps in early identification of breast cancer. This intelligent tool quickly delivers risk assessments, individualized screening programs, and preventative guidance, facilitating smarter, data-driven decisions in breast cancer care.

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Datasources

The assistant is trained on databases covering a wide range of data, such as historical patient outcomes and current clinical guidelines, ensuring comprehensive risk analysis. Sources include the Pan American Health Organization guidelines on breast cancer risk factors and prevention (3), summaries of the Colombian Ministry of Health clinical practice guideline on breast cancer (4), and detailed screening and treatment guidelines from the National Cancer Institute of Colombia (5). This content equips BreastAware with the information needed to guide medical specialists on screening and preventive strategies personalized to each patient's risk profile.

Citations

  1. American Cancer Society. (2021). Breast Cancer Facts & Figures 2021-2022. CA: A Cancer Journal for Clinicians, 71(3), 209-229. ACS Journals.
  2. Łukasiewicz S, Czeczelewski M, Forma A, Baj J, Sitarz R, Stanisławek A. Breast Cancer-Epidemiology, Risk Factors, Classification, Prognostic Markers, and Current Treatment Strategies-An Updated Review. Cancers (Basel). 2021 Aug 25;13(17):4287. doi: 10.3390/cancers13174287. PMID: 34503097; PMCID: PMC8428369.
  3. "Prevention: Breast Cancer Risk Factors and Prevention," Pan American Health Organization, Sep. 2016, Available: https://www.paho.org/en/documents/prevention-breast-cancer-risk-factors-and-prevention.
  4. "Executive Summary Clinical Practice Guide Breast Cancer," Ministry of Health Colombia, 2020.
  5. "Clinical Practice Guide (CPG) for early detection, comprehensive treatment, follow-up and rehabilitation of breast cancer," National Cancer Institute Colombia, n.d., Available: https://www.minsalud.gov.co/English/Paginas/Home.aspx.

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