How AI is Transforming Cancer Care in Ireland and Worldwide?

Aim of the study: This article explores the applications of AI in cancer management, focusing on Ireland, while drawing insights from global advancements. We will also examine the complexity of cancer, relevant statistics, and the application of AI in oncology.

Background

Cancer remains one of the most significant health challenges of our time. This life-altering disease affects millions of lives and families globally. According to CA: A Cancer Journal for Clinicians (2024), nearly 1 in 5 men or women will develop cancer in their lifetime. Around 1 in 9 men and 1 in 12 women will die from it, contributing to approximately 10 million deaths worldwide annually and leaving countless families to cope with the loss. Cancer has no age. Pediatric oncology, or childhood cancer, is a critical and delicate area of focus. While cancer is typically associated with adults, children are more vulnerable and require specialised care and treatment approaches, due to their unique developmental needs.

In the US, the National Cancer Institute states that 1 in 2 men and 1 in 3 women will develop cancer in their lifetime. The American Cancer Society’s (2025) Cancer Facts & Figures forecasts over 2 million new cancer diagnoses and 618,000 deaths in 2025.

While Ireland has a relatively lower cancer incidence rate, the Irish Cancer Society reveals that more than 44,000 people are diagnosed, and 9,800 die from it each year. Skin, prostate, breast, lung, and colorectal cancers are the most common. By 2045, the National Cancer Registry of Ireland (2019) predicts that the number of new cases could double. This is concerning, as it shows a growing trend. On a global scale, survival rates vary by individual. However, Irish Cancer Society estimates that 6 in 10 cancer patients in Ireland now survive for 5 years or more.

To address this, substantial investments are being made globally and in Ireland to combat this multifaceted disease. The study published in JAMA Oncology (2023) estimates that the global economic burden of cancer will be $25.2 trillion from 2020 to 2050. In 2025, the Irish government allocated ¤41 million to cancer services as part of the National Cancer Strategy 2017-2026. However, the financial burden extends beyond the public investment, as individuals also face heavy costs. The Irish Cancer Society (2019) reports that cancer patients incur significant additional expenses, averaging between ¤756 and up to ¤1,000 monthly.

In recent decades, artificial intelligence (AI) has begun transforming oncology. AI involves using algorithms to simulate human intelligence and perform tasks such as data analysis, pattern recognition, and decision-making. In oncology, AI uses computational algorithms and data-driven tools to improve cancer detection, diagnosis, and personalised treatment strategies. This emerging field, known as computational oncology, combines AI with cancer care to offer new solutions that aim to improve survival rates. By shifting away from trial-and-error methods, AI allows precise, science-backed approaches and helps reduce diagnostic errors. In addition to improving patient outcomes, AI has the potential to reduce healthcare costs. However, while its cost-effectiveness is promising, continued investments in development and access to high-quality data are needed to fully realise its potential.

Understanding Cancer Complexity

The human body contains approximately 30 trillion cells that grow, divide, and die, with new cells replacing them in a controlled cycle. When this process is disrupted, damaged cells multiply uncontrollably, causing mutations in DNA and altering cellular metabolism. This disruption leads to the Warburg effect, where cells rely on glycolysis for energy, even with oxygen present. In type 2 diabetes and obesity, insulin-like growth factors (IGFs), elevated glucose levels, and insulin resistance promote glycolysis, accelerating mutations and cellular disruptions. This creates an environment that supports abnormal cell growth and leads to tumor formation, increasing the risk of cancer. Tumors (lumps of tissue) can be benign or malignant, depending on how they grow and spread.

A benign tumor is a non-cancerous lesion that remains localised and does not invade nearby tissues. Although, it may become larger and presses on nearby organs, causing symptoms, it does not usually turn into cancer. Unlike malignant tumors, benign tumors do not follow the Stage I-IV classification system. Instead, they are usually classified based on size, location, and potential effects on the body. Examples include lipomas (fat tissue growths) and uterine fibroids.

In contrast, a malignant tumor is cancerous from the start and has the ability to spread, or metastasise, to distant parts of the body. Cancer often begins silently, without symptoms, and progresses through four stages. In Stage I, it is small and localised. In Stage II, it may grow or spread to nearby lymph nodes. In Stage III, it invades deeper tissues. By Stage IV, it spreads to distant organs. Malignant tumors are assessed using the TNM system for staging and grading to determine prognosis and guide treatment decisions.

Cancer originates from normal or progenitor cells that acquire genetic mutations. When mutations occur in stem cells, they can give rise to cancer stem cells (CSCs), which possess the ability to self-renew and create new cancer cells. These cells are often unpredictable and more resistant to traditional cancer treatments. CSCs can remain dormant during treatment and cause the tumor to regrow after therapy ends, contributing to relapses. They are believed to play a crucial role in tumor initiation, progression, and recurrence.

There are more than 100 types of cancer, usually named after the organs or tissues where they form, such as brain cancer or pancreatic cancer. Cancer can originate in any organ or tissue without exception. The cancer types can be further categorised based on the specific tissue or cell type involved, like carcinomas (epithelial cells), sarcomas (connective tissues), leukemias (blood-forming tissues), lymphomas (lymphatic system), and others. Viruses cause about 20% of tumors worldwide (American Society for Microbiology, 2019). These include Epstein-Barr virus (Burkitt’s lymphoma), HPV (anogenital cancer), HBV and HCV (liver cancer), Helicobacter pylori (stomach cancer), HHV-8 (Kaposi’s sarcoma), MCPyV (Merkel’s sarcoma), HIV-1 (Kaposi’s sarcoma, cervical cancer), and CMV (glioblastoma). Helminths like Schistosoma (bladder cancer) and Clonorchis (gallbladder cancer) also play a role.

Cancer and cardiovascular diseases (CVDs) share common risk factors, including stress, smoking, obesity, physical inactivity, chronic infections, and an unhealthy diet. Additionally, certain cancer treatments can harm heart health. Chemotherapy and radiation therapy, for example, may lead to cardiomyopathy, arrhythmias, and coronary artery disease (Mayo Clinic Proceedings, 2020). Consequently, cancer survivors face a higher risk of CVDs, with cardiovascular mortality sometimes surpassing cancer-related deaths (BMJ Oncology Journal, 2023).

The exact cause of cancer is not fully understood. However, several factors contribute to its development:

• Genetics plays an important role, especially inherited mutations in genes like BRCA1 and BRCA2. These genes normally repair damaged DNA, but when mutated, they increase the risk of cancers, such as breast and ovarian cancer. The effects of these mutations typically do not show up until until adulthood, often appearing in the 30s or 40s.
• Random mutations, often influenced by poor lifestyle choices (smoking, unhealthy diet) or environmental exposures (excessive UV exposure, radiation), lead to changes in genes like TP53, which help control cell division.
• Familial factors, a mix of genetic and environmental influences, also increase cancer risk. For example, Familial Adenomatous Polyposis (FAP) is caused by a mutation in the APC gene, which regulates cell growth.

As a complex disease, cancer exists in multiple forms, which makes diagnosis and treatment challenging. In many cases, a cancer diagnosis means an uncertain future, with some types being treatable while others are less so. Unfortunately, a significant percentage of cancer cases are diagnosed at advanced stages (III or IV), where treatment options are limited and survival rates are lower. Cancer treatments are still expensive and sometimes ineffective. Moreover, one-size-fits-all approach to treatment has proven to be insufficient. Cancer requires a more personalised strategy based on the unique characteristics of each case. Precision medicine can complement or replace the traditional approach. By integrating AI into early detection, diagnostics, and treatment planning, we can enhance our understanding of cancer’s complexity and improve outcomes through more precise and timely interventions.

Ireland’s and Global Efforts in AI Oncology

Ireland, along with leading institutions in the United States, Australia, Asia, and Europe, is actively working to implement AI-powered tools to transform oncology. Irish hospitals and research institutions are making pioneering efforts in the integration of AI into oncology, promising a long-lasting impact both locally and globally. University College Dublin (UCD) is at the forefront of multiple initiatives aimed at enhancing early detection, diagnostics, and treatment through machine learning and AI algorithms. Notably, UCD’s Systems Biology research centre coordinates Precision Oncology Ireland (POI), a consortium of Irish universities, cancer research charities, and international companies. Additionally, All-Island Cancer Research Institute (AICRI) brings together ten academic institutions (UCD, TCD, UL, RCSI, TU Dublin, DCU, QUB, UU, NUIG, and UCC) and maintains a transatlantic partnership with Roswell Park Comprehensive Cancer Center in Buffalo, New York. While AI adoption in Ireland is still in its early stages, research partnerships, clinical trials, and collaborations with global companies are accelerating progress in both urban and rural settings.

Similarly, top institutions worldwide are making groundbreaking strides in AI-driven cancer management. In the U.S., the Mayo Clinic has created an AI model capable of detecting pancreatic cancer in CT scans as much as 475 days before a clinical diagnosis. It also uses AI-driven virtual reality platforms to transform CT and MRI scans into 3D models for better surgical planning. The University of California, San Francisco, together with IBM Research, has paired machine learning with cellular engineering. Using AI, they created a virtual molecular library, helping engineered immune cells target and eliminate cancer cells. This is done by providing cells with thousands of “command sentences”.

In Australia, the University of Sydney, in collaboration with Pharos Therapeutics, is advancing AI in oncology by developing AI-powered imaging technologies for early detection and cancer treatment. They are leading a $10 million project focused on large-scale 3D imaging trials for melanoma and skin cancer to create next-generation solutions.

In Japan, the National Cancer Center (NCC) integrates AI into CT scan analysis for more accurate detection of lung and gastric cancers. In collaboration with other institutions, NCC participates in initiatives like LC-SCRUM-Asia, which focuses on genetic screening of lung cancer patients across Asia. Furthermore, NCC has launched the MONSTAR-SCREEN-2 project, which uses multi-omics analysis powered by AI to better understand cancer. This approach incorporates whole-exome and whole-transcriptome sequencing to analyse DNA and RNA from tumor tissues, aiming to enhance cancer diagnostics and treatment planning.

In Germany, the German Cancer Research Center (DKFZ) employs AI to analyse large-scale genomic data to advance personalised cancer immunotherapies by identifying tumor-specific “neoepitopes” through mass spectrometry. Charité – Universitätsmedizin Berlin is exploring AI in pathology and leading the EMPAIA project to develop AI-assisted diagnostic imaging solutions. Moreover, they research cancer survivorship.

These global efforts demonstrate the transformative power of AI in cancer care.

Bringing AI to Patients in Ireland: Early Detection and Diagnostics

Over-diagnosis leads to unnecessary treatments, causing side effects, stress, and financial burden. Meanwhile, under-diagnosis delays care. AI helps identify patients who truly need early interventions, reducing both risks. By integrating AI into cancer diagnostics, Ireland is making significant strides toward earlier detection, more precise treatments, and a more efficient healthcare system.

Traditional methods of diagnosing cancer, such as imaging, physical exams, biopsy, and laboratory tests, have long faced limitations. They often struggled to identify early-stage cancers, detect subtle abnormalities, and provide personalised, scalable care. While effective in many cases, these methods rely heavily on human assessment, making them prone to human error and fatigue. For example, X-rays, mammograms, ultrasounds, CT scans, MRI scans, are crucial in detecting tumors, but require radiologists to manually interpret images, which increases the risk of missed diagnoses. Similarly, physical exams, such as self-checks and doctor-led palpation, can help detect lumps but fail to identify microscopic tumors or asymptomatic cases. Biopsy procedures are accurate but invasive and may not capture the full extent of metastasis. Likewise, blood tests measuring tumor markers lack specificity, making them unreliable as standalone diagnostic tools.

In Ireland, the integration of AI in oncology has evolved, particularly in radiology and pathology:

• The Mater Misericordiae University Hospital in Dublin has become the first public hospital in Ireland to implement AI in Radiology. Since the introduction, over 15,600 scans have been analysed, with 700+ pathologies correctly flagged within 2-3 minutes.
• The University of Limerick (UL) and Dell Technologies have partnered to develop an AI platform and digital twin technology (computational replicas of patients’ cellular environments) for cancer research, enabling simulations to predict disease progression and treatment responses, particularly for B-cell lymphoma.
• The University of Galway’s Insight Centre for Data Analytics has created SKnowGPT, a system enhancing Large Language Models (LLMs) with domain-specific Knowledge Graphs. This improves AI’s ability to answer complex medical queries accurately.
• The Classica project, led by Professor Ronan Cahill and partners, aims to refine AI-driven imaging for real-time cancer surgery decisions using fluorescence imaging.
• Systems Biology Ireland focuses on cellular signaling networks for new cancer therapies. Their work combines multi-omics data, wet-lab experiments, and computational modeling to identify key cancer-related genes to facilitate personalised treatments.
• The CLARIFY project, funded by Horizon Europe, uses AI to analyse data from cancer survivors to improve follow-up care and early detection.
• POI uses computational modeling to develop more accurate diagnostic tests and personalised treatments.
• AI systems like DeepMind and IBM’s Watson for Oncology, used globally and in Ireland, assist radiologists and pathologists by automating image analysis and tissue sample evaluation. They highlight potential issues, reduce waiting times and improve diagnostic accuracy.

AI is transforming cancer diagnostics in biopsy analysis in Ireland. Deciphex, a Dublin-based company, uses AI-powered platforms like Diagnexia and Patholytix to assist pathologists. These tools improve tissue sample analysis, diagnostic speed, and accuracy, while reducing workloads. Deciphex’s platforms are used by the Health Service Executive (HSE) and National Health Service (NHS) and are expanding into North America.

Additionally, the OncDB platform, developed by Mr. Michael McCarthy at University Hospital Galway, uses AI to analyse clinical trial data, helping professionals stay updated with the latest cancer treatments. The DigiCanTrain project at the University of Galway provides digital skills training for oncology professionals. It integrates AI and digital tools into cancer care education.

Between 2019 and 2022, over ¤106 million was invested in cancer research in Ireland, with contributions from eight funders. However, the prevention category received only ¤2.8 million, or 2.7% of the total funding (Health Research Board, 2024). This underfunding could delay AI integration into cancer management. Prevention programs, such as screening, vaccination, and early diagnostic systems, generate vast amounts of structured, high-quality data for AI analysis, which is crucial for predicting cancer risks and training models. Early interventions are also cost-effective, reducing future healthcare burdens. The Health Service Executive (HSE) is exploring AI for national screening programs like BreastCheck and CervicalCheck. National Screening Service (NSS) is assessing AI-driven models to identify high-risk individuals and prioritise screenings.

Personalised Treatment Planning in Ireland

Over-treatment can expose patients to unnecessary side effects, while under-treatment risks disease progression. AI aims to address these gaps with tailored, data-driven approaches. Traditional methods of treating cancer like surgery, chemotherapy, and radiation are now complemented by targeted, metabolic, immune, CAR-T therapies, and more. In Ireland, AI-driven precision medicine is advancing personalised cancer care by analysing genetic data, tumor profiles, patient histories, and identifying biomarkers, to recommend optimal treatments. AI is also crucial in drug discovery, treatment tracking, and clinical trial recruitment – predicting therapy responses and matching patients to appropriate trials.

• In Ireland, institutions like the Irish Cancer Society and Trinity College Dublin are using AI to improve the clinical trial process. AI analyses data from patient records, imaging, and genetic tests to identify trends and support the development of new drugs. This helps researchers discover more effective therapies for challenging cancers like pancreatic and brain cancers.
• The University of Galway is also leading initiatives like the NEO-TIL project. This project develops novel immune therapies for cancers with high mutation rates.
• Led by POI, the cSTAR platform, another notable initiative, creates digital twins to predict patient responses to drug interventions, improving outcomes and minimising side effects.
• Other projects include COLOSSUS, which advances precision medicine for metastatic colorectal cancer.
• There is also 3TR, an IMI2 immunology project, focused on improving disease management across seven immune-mediated diseases.
• The Royal College of Surgeons in Ireland (RCSI) is conducting cutting-edge research on AI’s role in cancer genomics.

Telemedicine in Ireland

Telemedicine is the remote delivery of cancer care, using technology like video consultations, AI platforms (e.g., IBM Watson Health, Babylon Health), and wearable devices (e.g., smartwatches, biosensors). It allows oncologists to monitor patients, provide consultations, and adjust treatments without in-person visits. This is crucial in rural areas with limited healthcare access. The aging population and healthcare professional shortages make remote solutions essential. Telemedicine ensures patients receive timely, continuous care despite geographical barriers.

Additionally, the FAITH project in Ireland offers the “AI Angel” app, which monitors mental health in cancer survivors. This app helps them manage the psychological impact of their diagnosis and treatment.

Ethical Considerations and Who Is Responsible for AI Mistakes in Oncology?

AI integration in oncology is governed by the GDPR in Ireland and across Europe. This ensures patient privacy and data protection. In the US, HIPAA ensures data privacy, while the FDA oversees AI medical devices. Australia follows the Privacy Act 1988, and Asia has diverse regulations like APPI (Japan).

When systems make mistakes in healthcare, especially in oncology, accountability can be complex. In Ireland and globally, the responsibility typically falls on a combination of stakeholders. Healthcare providers, such as doctors and specialists, are accountable for interpreting and acting on system recommendations. If AI or technology is involved, the developers or creators of the system could share accountability for ensuring their products are tested, accurate, and reliable. Regulatory bodies also play a role in setting standards and guidelines. Ultimately, when errors occur, accountability may involve both human and technological factors, with each party held responsible for their part in the decision-making process.

Conclusion

Progress in pediatric and adult oncology, driven by research and innovation, offers hope for better outcomes across all ages worldwide. By integrating AI into healthcare, Ireland is well-positioned to lead in AI-powered oncology. Its promising future is marked by breakthroughs in diagnostic tools, genetic analysis, and precision medicine, supported by ongoing research and collaboration. AI will play a crucial role in early detection, personalised treatments, and innovations like autonomous AI oncologists and robotic surgery. However, the success of these innovations depends on access to quality data, including medical records, imaging scans, and medical tests. Donating such data to research, while ensuring it is anonymised and kept private, will fuel AI advancements. Nations around the world are increasingly adopting AI in the fight against cancer. Collective efforts contribute to the broader global push to improve cancer treatment and patient outcomes.

Written by Olivia Iarmak https, Data Labeling Analyst at Meta, linguist, author – and Tatiana Iarmak, Epidemiologist, author, speaker, consultant. Former lecturer at Kharkiv Regional Medical Professional College.

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