Leveraging AI to Detect Cancer Early | Social Determinants May Increase Risk for Cancer
Updated: Apr 25, 2022
Cancer is a serious public health concern worldwide. As the second leading cause of death in the United States, it affects every socio-economic stratum. Nevertheless, certain groups bear a disproportionate burden of cancer due to social, environmental and economic disadvantages.
How population groups are being impacted by cancer?
Population groups that may experience such disparities include groups defined by race/ethnicity, disability, gender identity, geographic location, income, education, age, sexual orientation, national origin, and/or other characteristics.
According to the Cancer Statistics Center, there will be an estimated 1,898,160 new cancer cases and 608,570 cancer deaths in 2021 in the US alone. That amounts to approximately 5,200 new cases and 1,670 deaths every day. (As the COVID-19 pandemic burdened healthcare systems in 2020, experts fear delay in cancer diagnosis and treatments may lead to even higher numbers by year-end.) Yet, many of these incidences can be avoided by healthy lifestyle choices, better access to resources, and enhanced public health measures. Critically, the intersection of AI and Health is enabling detection in early stages of cancer.
Can Cancer be detected and cured early?
Worldwide, many healthcare organizations have realized the importance of electronic health records for predictive analytics. Although much of the existing clinical data is currently stored in silos, organizations are taking active efforts towards unifying the data collection and storage system. Artificial intelligence can play an important role in fighting cancer at every stage of disease progression ranging from detecting cancer early to finding the best palliative care in the late cancer stages. AI excels at identifying patterns in big volumes of data and finding complex relationships in data features that are difficult to identify manually.
For example, imaging data in screening can be used to detect patterns associated with early breast cancer. Demographic data and other socio-economic data can be assessed to address the disparities in the rate of morbidity and mortality, survival time, and the like.
Further, AI can help bridge healthcare disparity gaps by incorporating factors such as social determinants of health. Data from clinical studies, scientific literature and research databases can be utilized to find optimum personalized treatment plans to treat specific diseases. Improved patient outcomes in addition to reduced physician burden can be achieved with the assistance of AI.
How far has the healthcare industry progressed to detect cancer early?
In the coming years, the field of Artificial Intelligence will be a game-changer for US healthcare. The possibility of extracting meaningful information from structured and unstructured healthcare data provides a basis for redefining healthcare and improving overall population health outcomes. We are CognitiveCare... Under the guidance of leading healthcare professionals, practicing oncologists and collaboration with healthcare providers, pharma and life-sciences – we are equipped with all the skills and expertise required to make it happen sooner.
Collectively, our interdisciplinary team of professionals have experience in data science, biology, genomics, healthcare and public policy to lead the revolution of improved population health outcomes through early detection and prevention for all.
Request Demo, to know more about CognitiveCare's cancer-detecting approach.