In 2021, cancer was the second leading cause of death in the European Union. Notably, while Europe constitutes only a tenth of the global population, it accounts for almost a quarter of the world's cancer cases, bearing an economic impact of approximately 100 billion annually. Belgian statistics further highlight that every step forward in cancer treatment and care could significantly alleviate the immense personal and societal burden. Globally, extensive efforts are made through a variety of innovative approaches with the ultimate objectives of better prevention, earlier detection, and improved patient outcomes and care. Personalized medicine is considered the holy grail of cancer care in most of these initiatives. Tailoring interventions to the unique characteristics of individual patients promises to revolutionize cancer care. Artificial intelligence (AI) plays a pivotal role in this transformative journey towards precision medicine, aiding researchers and healthcare professionals in accurately predicting cancer risks, enabling earlier diagnoses, and customizing treatment plans to meet individual needs.

After 17 years of serving his country, Mark Kelm is now providing a different type of service: He's advocating for others who, like him, are living with Parkinson's disease. He's shown in the family picture at left, center, plus on the right. 'A NEW KIND OF SERVICE' – After 17 years in the military, a Minnesota man received a shocking diagnosis – and is now committed to helping others with the same disease. PERFECT MATCH – A young girl with acute leukemia is now in cancer remission thanks to her sister's lifesaving bone marrow donation. CANCER PREDICTIONS – Can artificial intelligence predict whether cancer treatments will work?

Many are aware of the Cancer Moonshot--an ambitious and hopeful initiative of the U.S. government to reduce cancer-related death rates by 50% by the year 2047. It will take an army to achieve this goal, composed of the brightest minds and biggest hearts in healthcare, science, and technology. Many parties will be involved--the federal government, healthcare providers, researchers, patients, caregivers, and advocates, among others in both the public and private sectors. One of the most pivotal tools that can help propel us toward this lofty goal is artificial intelligence (AI), which is poised to revolutionize cancer treatment. The moonshot plan identifies five priority areas, all of which AI has the potential to enhance. Two areas in particular lend themselves to AI: the call to "deliver the latest cancer innovations to patients and communities" and the aim of enhancing "the oncology model to place cancer patients at the center of decision-making."

Cancer is a disease that affects millions of people worldwide. According to the World Health Organization (WHO), cancer is the second leading cause of death globally, after cardiovascular diseases. In 2018, about 9.6 million deaths were reported due to cancer. The WHO estimates that over 1.8 million people died from cancer in 2017. The number of new cases of cancer is expected to increase by 70% between 2015 and 2030.

Now, we trust the complex processes underlying artificial intelligence (AI) with everything from navigation to movie recommendations to targeted advertising. Can we also trust machine learning with our health care? The integration of AI and cancer care was a popular topic in 2021, as evidenced by prominent sessions at two of last year's AACR conferences: the 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved, held virtually October 6-8, 2021, and the San Antonio Breast Cancer Symposium (SABCS), held in a hybrid format December 7-10, 2021. During these sessions, experts gave an overview of how machine learning works, shared data on new applications of AI technologies, and emphasized important considerations for making algorithms equitable. Recognizing that a diverse audience of breast cancer clinicians and researchers may have questions about the fundamentals of AI, the SABCS session "Artificial Intelligence: Beyond the Soundbites" opened with a talk titled, "Everything You Always Wanted to Know About AI But Were Afraid to Ask," presented by Regina Barzilay, PhD, the AI faculty lead at the Jameel Clinic of the Massachusetts Institute of Technology.

In 2019, there were approximately 23.6 million new cancer cases and 10 million cancer deaths globally, which represents a 26.3% increase in new cases and a 20.9% increase in fatalities compared with 2010. Furthermore, COVID-19 has had devastating effects on patients with cancer, with massive numbers of delayed diagnoses and treatments due to the constraints COVID-19 has put on health systems. As the pandemic normalizes, global communities look to re-prioritize – ensuring quality and equitable access of cancer diagnostics, treatment and care. We believe the technologies of the fourth industrial revolution (4IR) can address some of the most significant challenges that humanity faces today. The World Economic Forum is working with partners globally to close the gap in premature death by lung cancer and to leverage new technologies to improve and transform cancer care in India.

Healthcare technologies have seen a surge in utilization during the COVID 19 pandemic. Remote patient care, virtual follow-up and other forms of futurism will likely see further adaptation both as a preparational strategy for future pandemics and due to the inevitable evolution of artificial intelligence. This manuscript theorizes the healthcare applications of digital twin technology. Digital twin is a triune concept that involves a physical model, a virtual counterpart, and the interplay between the two constructs. This interface between computer science and medicine is a new frontier with broad potential applications. We propose that digital twin technology can exhaustively and methodologically analyze the associations between a physical cancer patient and a corresponding digital counterpart with the goal of isolating predictors of neurological sequalae of disease. This proposition stems from the premise that data science can complement clinical acumen to scientifically inform the diagnostics, treatment planning and prognostication of cancer care. Specifically, digital twin could predict neurological complications through its utilization in precision medicine, modelling cancer care and treatment, predictive analytics and machine learning, and in consolidating various spectra of clinician opinions.

A 65-year-old man with a remote smoking history is automatically referred to your clinic after an artificial intelligence (AI) algorithm-enhanced routine CT screening exam detects a nodule with 90% certainty of malignancy. A 45-year-old woman with metastatic breast cancer arrives at your office and her AI-integrated electronic health record (EHR) algorithm alerts you that she has a 60% probability of a major cardiac event within 5 years if given an anthracycline. You hold an uninterrupted, computer screen–free discussion with your patient about their newly diagnosed pancreatic cancer; meanwhile, an AI-powered device processes the conversation and produces all documentation and billing information. Only a few years ago, these imagined scenarios may have seemed far-fetched, but no longer. Increasingly, and with exponential pace, AI algorithms are finding their way into the oncology clinic.

The next generation of cancer therapies may be discovered by melding data science technologies with cancer research. It can be used to speed up research, provide additional insights and therapeutic alternatives, and eventually improve patient care. Cloud computing provides almost infinite resources for storing, analyzing, and displaying data. Genomic databases can be analyzed without a local infrastructure to house the enormous data volumes. Since machine learning relies on a huge number of samples, the cloud can support it by enabling access to big data sets from many sources.

Artificial intelligence (AI) is everywhere: personal digital assistants answer our questions, robo-advisors trade stocks for us, and driverless cars will someday take us where we want to go. AI has penetrated our lives, and its use is exploding in biomedical research and health care--including across all dimensions of cancer research, where the potential applications for AI are vast. Artificial Intelligence (AI) is a computer performing tasks commonly associated with human intelligence. Humans are coding or programing a computer to act, reason, and learn. An algorithm or model is the code that tells the computer how to act, reason, and learn.