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Breast Cancer

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


Breast cancer, also known as breast cancer, is a disease in which malignant cells form in the tissues of the breast. The breast is composed of mammary glands, ducts, and fatty tissue. Breast cancer can develop in any of these areas and, over time, spread to nearby tissues or other body parts through the lymphatic system or bloodstream. Breast cancer is more common in women but can also affect men (1). Risk factors include a family history of breast cancer, genetic mutations, advanced age, long-term exposure to female hormones, obesity, and heavy alcohol use (2).

Symptoms can vary, but the most common include a lump in the breast, changes in the size or shape of the breast, changes in the skin covering the breast, redness, scaling, or ulceration, discharge from the nipple, and changes in nearby lymph nodes. Early diagnosis and prompt treatment are crucial to improving breast cancer survival rates. Detection methods include breast self-examination, mammography, breast ultrasound, and MRI. Treatment may involve surgery, radiation therapy, chemotherapy, hormone therapy, and targeted therapy, depending on the cancer stage and the patient's characteristics. Proper detection, treatment, ongoing research, and support for patients and families are critical in the fight against breast cancer (3).

Size of the Problem

  • In 2022, an estimated 281,360 new cases of invasive breast cancer and 48,930 new cases of in situ breast cancer (DCIS) will be diagnosed in women in the United States (1).
  • About 43,240 women in the United States will die from breast cancer in 2022 (1).
  • Breast cancer is the most common cancer diagnosed in women, except for skin cancers other than melanoma (2).
  • About 1 in 8 women (12%) will develop invasive breast cancer throughout their lifetime (3).
  • The risk of developing breast cancer increases with age. About 75% of breast cancers are diagnosed in women aged 55 or older (4).

Why it matters

Breast cancer poses a significant health problem for the population, hospitals, the healthcare system, and society. It is the most common form of cancer in women, and although it also affects men, its incidence is much lower. This disease carries a substantial burden at both the individual and collective levels. On a personal level, breast cancer can devastate the lives of affected individuals and their families (2). It involves prolonged treatments, invasive surgeries, aggressive therapies such as chemotherapy and radiation, and possible adverse side effects. Breast cancer diagnosis carries a considerable emotional burden and can generate anxiety, depression, and concerns about the future (3).

In hospitals and the healthcare system, breast cancer presents a significant challenge. It requires substantial resources, such as specialized medical personnel, diagnostic and treatment equipment, and long-term follow-up programs. Early diagnosis and timely treatment are crucial to improving outcomes and increasing survival rates. However, access to quality healthcare services may be limited in specific regions or for disadvantaged populations, making it challenging to address breast cancer effectively. Furthermore, the rise in this disease has put pressure on healthcare systems, resulting in long waiting lists, delays in diagnosis, and challenges in providing comprehensive and continuous care to patients. Ultimately, breast cancer represents a social challenge as it affects not only the individuals who experience it but also their families and communities. Raising awareness about early detection and promoting healthy lifestyles is crucial to addressing this issue and reducing its impact on society (4).


Artificial Intelligence (AI) can potentially revolutionize the approach to breast cancer by addressing various challenges faced by patients, hospitals, the healthcare system, and society. Firstly, AI can significantly contribute to early detection and diagnosis of breast cancer. By analyzing mammograms and patient data, AI algorithms can assist radiologists in identifying potential signs of breast cancer at an early stage, leading to timely interventions and improved treatment outcomes.

Secondly, AI can enable personalized treatment planning for individuals diagnosed with breast cancer. AI algorithms can identify patterns and develop tailored treatment plans by analyzing large datasets that include genetic profiles, medical records, and treatment outcomes. This personalized approach ensures that patients receive targeted and effective therapies, maximizing the chances of successful treatment.

Furthermore, AI-powered predictive analytics can assist healthcare providers in making informed decisions regarding patient care and prognosis. AI can predict disease progression and patient outcomes by analyzing various patient factors, such as medical history, genetic information, and lifestyle. This information helps healthcare professionals optimize treatment strategies, allocate resources effectively, and provide proactive interventions for individuals at higher risk of developing breast cancer.


  • Hospital Information System (HIS): If you work in a hospital, you can leverage the internal HIS to access relevant clinical data such as electronic health records, laboratory reports, medication records, and diagnostic test results. This data can be valuable for research, outcome prediction, and identifying patterns related to breast cancer.
  • Electronic Medical Records (EMR): EMRs are an essential source of clinical data that contain detailed information about patients, including medical history, test results, diagnoses, and treatments. These records can assist in identifying risk factors, evaluating treatment effectiveness, and monitoring breast cancer progression.
  • Clinical Trial Databases: Some pharmaceutical companies and hospitals maintain databases of ongoing or completed clinical trials related to breast cancer. These data can provide information on the efficacy and safety of different treatments, demographic data, and patient outcomes involved in the trials.
  • Genomic Databases: Genomic sequencing of breast cancer has revealed valuable information about genetic alterations and molecular characteristics associated with the disease. You can utilize genomic databases to access this information and better understand the underlying biology of breast cancer, identify new therapeutic targets, and develop personalized therapies.
  • Pharmacovigilance Databases: These databases collect information on adverse effects and drug safety in breast cancer treatment. You can use this data to assess the safety and efficacy of existing medications and identify potential adverse effects or drug interactions.


  1. (n.d.). Facts & Statistics. Retrieved from
  2. Centers for Disease Control and Prevention. (n.d.). Basic Information About Breast Cancer. Retrieved from
  3. American Cancer Society. (2021). Breast Cancer Facts & Figures 2021-2022. CA: A Cancer Journal for Clinicians, 71(3), 209-229. ACS Journals
  4. 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.

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