Preventive Oncology and Diagnostic Cancer

Molecular foundations are reshaping preventive oncology by enabling earlier identification of individuals at elevated cancer risk before clinical symptoms appear. Advances in genomics, epigenomics, transcriptomics, and proteomics now support highly sensitive detection of pre-malignant alterations and inherited susceptibility patterns. Hereditary cancer syndromes, germline mutation testing, and the integration of high-penetrance and moderate-risk genes into clinical workflows are strengthening personalized prevention strategies. The expanding use of polygenic risk scores, supported by large population datasets, allows refinement of individualized screening intervals and targeted surveillance models. Liquid biopsy technologies, including circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), microRNA signatures, and extracellular vesicles, are transforming noninvasive early detection and minimal residual disease monitoring. Epigenetic biomarkers such as DNA methylation signatures and chromatin modification patterns further enhance sensitivity in early-stage cancer identification. Preventive interventions including chemoprevention, targeted prophylactic therapies, immunoprevention strategies, and vaccine development are increasingly aligned with molecular risk profiling. Translational research pipelines emphasize analytical validation, reproducibility, and clinical utility to ensure safe implementation of emerging biomarkers. Ethical considerations including genetic counseling, informed consent, and responsible communication of probabilistic risk remain central to integrating molecular diagnostics into preventive frameworks. By combining molecular biology, predictive analytics, and precision medicine approaches, proactive cancer prevention strategies are shifting oncology from reactive treatment models toward anticipatory, individualized care designed to reduce long-term cancer burden.

The convergence of multidisciplinary diagnostic technologies is enhancing the accuracy, efficiency, and personalization of early cancer detection. Multimodal platforms integrating molecular profiling, advanced imaging, digital pathology, and artificial intelligence–driven analytics are creating cohesive diagnostic ecosystems capable of identifying malignancies at earlier stages. Multi-cancer early detection assays capable of detecting multiple tumor types from a single blood sample are expanding screening possibilities beyond organ-specific approaches. Radiomics and imaging biomarkers, when combined with genomic and proteomic signatures, improve sensitivity and specificity while reducing diagnostic uncertainty. Digital pathology systems with automated tumor grading and AI-assisted slide interpretation are minimizing variability and accelerating clinical workflows. Innovations in point-of-care testing, wearable biosensors, and remote monitoring technologies are expanding access to preventive services, particularly in resource-limited settings. Seamless interoperability between laboratory systems, imaging platforms, and electronic health records supports integrated clinical decision-making. Consideration is given to challenges such as overdiagnosis, incidental findings, and patient communication complexities associated with advanced screening tools. Alignment of laboratory science, digital infrastructure, and clinical expertise ensures that diagnostic advancements translate into meaningful patient outcomes. Comprehensive integration of these technologies establishes a patient-centered early detection framework designed to improve survival while optimizing healthcare efficiency.

Emerging technologies are revolutionizing early cancer detection by enabling the identification of pre-malignant and early malignant changes with unprecedented precision. Single-cell sequencing, spatial transcriptomics, and multi-omics integration allow researchers and clinicians to map cellular heterogeneity, detect rare oncogenic events, and understand tumor evolution at the earliest stages. Advanced proteomics and metabolomics profiling further enhance the ability to detect subtle molecular shifts that may precede overt cancer development. Nanotechnology-based biosensors and microfluidic platforms are enabling rapid, highly sensitive biomarker analysis with minimal invasiveness. Integration of radiomics and pathomics into unified diagnostic pipelines allows comprehensive characterization of tumors from noninvasive imaging combined with digital pathology, improving predictive accuracy and treatment planning. Artificial intelligence and machine learning algorithms are increasingly applied to detect subtle patterns across complex datasets, from imaging scans to molecular profiles, facilitating early identification of high-risk individuals. Longitudinal monitoring using real-world data and wearable technologies supports adaptive surveillance strategies, enabling dynamic risk assessment over time. Ethical considerations, including validation standards, regulatory compliance, and equitable access, are critical to ensuring that these advanced diagnostics are implemented safely and responsibly. By combining cutting-edge laboratory innovations, computational analytics, and translational research, these emerging technologies offer a transformative approach to preventive oncology, enabling proactive intervention and improved outcomes while reducing cancer-related morbidity and mortality.

The development and translation of cancer biomarkers into clinical practice require rigorous validation and quality assurance frameworks to ensure reliability, reproducibility, and clinical utility. Biomarker pipelines include discovery, analytical validation, clinical validation, and demonstration of clinical effectiveness, with each stage requiring robust methodologies to reduce false positives and false negatives. Standardization across laboratories, including harmonized assay protocols, quality control measures, and proficiency testing, ensures that biomarkers perform consistently in diverse settings. Integration of biomarkers into clinical workflows supports risk-adapted prevention, early detection, and treatment decision-making, particularly when combined with imaging and molecular profiling. Biobanking infrastructure, longitudinal cohort studies, and real-world evidence collection are critical for validating biomarkers across populations and understanding long-term outcomes. Regulatory pathways and ethical considerations, including informed consent for genetic testing and data privacy, underpin safe translation of biomarkers into clinical use. Companion diagnostics and predictive biomarkers enhance preventive strategies by identifying individuals who are most likely to benefit from targeted interventions or chemopreventive therapies. Data integration across laboratory systems, electronic health records, and clinical decision-support platforms facilitates a seamless diagnostic continuum. By bridging discovery science with translational and implementation frameworks, validated biomarkers serve as essential tools for precision prevention and personalized early cancer detection strategies.

Sustainable cancer prevention requires the alignment of health policy, healthcare systems, and population-level interventions to embed early detection and risk reduction into routine care. National and regional frameworks must address reimbursement models, funding mechanisms, and public–private partnerships to support large-scale screening programs. Integration of preventive oncology into primary care, multidisciplinary teams, and community health initiatives ensures coordination across clinicians, genetic counselors, radiologists, and public health professionals. Workforce development, infrastructure enhancement, and training in emerging diagnostic technologies are critical to expanding access, especially in low-resource or underserved regions. Community engagement strategies, culturally tailored health education, and patient navigation programs increase participation in screening and adherence to preventive interventions. Digital health platforms, centralized cancer registries, and interoperable data systems enable continuous monitoring, evaluation, and real-time adjustment of preventive programs. Policy and regulatory frameworks are essential to ensure ethical implementation, equity in access, and cost-effectiveness. By combining health system planning, evidence-based guidelines, and global collaboration, sustainable preventive oncology programs can reduce cancer incidence, improve early detection rates, and strengthen long-term population health outcomes worldwide.

Artificial intelligence (AI) and predictive analytics are transforming early cancer detection by enabling the analysis of complex datasets that surpass human interpretative capacity. Machine learning, deep learning, and neural network algorithms are applied across radiology, pathology, genomics, and electronic health records to identify subtle patterns indicative of early malignancy. AI-assisted mammography, low-dose CT interpretation for lung cancer, digital pathology slide analysis, and predictive risk scoring systems facilitate earlier and more accurate detection while reducing interobserver variability. Predictive models integrate longitudinal patient data, molecular biomarkers, and lifestyle factors to forecast individualized cancer risk trajectories and recommend personalized screening intervals. Federated learning approaches allow multi-institutional collaboration without compromising patient privacy, while bias mitigation strategies ensure equitable performance across diverse populations. The integration of wearable health monitoring devices, cloud-based diagnostic platforms, and real-world data further enhances the predictive capabilities of AI-driven systems. Ethical considerations including transparency, explainability, patient consent, and regulatory oversight are central to responsible AI deployment in clinical practice. By combining computational analytics with clinical insights, AI enables proactive cancer surveillance, improves diagnostic efficiency, and supports precision prevention strategies, ultimately reducing morbidity and mortality through earlier intervention and targeted monitoring.

Community engagement and public health integration are critical for effective cancer prevention, focusing on behavioral interventions, risk reduction, and equitable access to early detection services. Lifestyle modifications such as tobacco cessation, healthy diet, physical activity, and vaccination programs significantly reduce cancer risk at the population level. Community-based initiatives, patient navigation programs, and culturally tailored education campaigns improve screening uptake, particularly in underserved and rural populations. Integration of preventive oncology into primary care, school-based health programs, and workplace wellness initiatives supports widespread adoption of risk reduction practices. Digital health technologies, mobile applications, and telehealth platforms extend the reach of prevention programs and enable real-time monitoring and follow-up. Public health policies, environmental interventions, and long-term strategic planning further enhance population-level impact. Addressing socioeconomic, geographic, and cultural disparities ensures equitable access to preventive services and reduces health inequities. Data collection, cancer registries, and outcome monitoring facilitate program evaluation, continuous improvement, and evidence-based policy decisions. By combining behavioral science, public health strategies, and community partnerships, these approaches create sustainable frameworks for reducing cancer incidence, promoting early detection, and improving long-term health outcomes on a population scale.

Advances in immunology are opening new frontiers in preventive oncology, focusing on strategies to harness the immune system to intercept cancer before it develops. Personalized immunoprevention involves tailoring vaccines or immune-based interventions to individual molecular and genetic risk profiles, targeting tumor-associated antigens or neoantigens specific to high-risk populations. The development of prophylactic cancer vaccines, such as those for virus-associated malignancies (e.g., HPV and hepatitis B), provides a model for extending immunoprevention to non-viral cancers through emerging peptide, mRNA, and dendritic cell vaccine platforms. Immune checkpoint modulation and adoptive immune therapies are being explored as preventive approaches in individuals with precancerous lesions or high-risk genetic mutations. Biomarker-guided immune monitoring enables real-time assessment of immune response and efficacy, facilitating adaptive immunoprevention strategies. Ethical, regulatory, and safety considerations, including long-term immune surveillance and risk-benefit assessment, are critical in clinical implementation. Translational research pipelines integrate preclinical models, early-phase clinical trials, and population-level studies to validate vaccine effectiveness and guide deployment strategies. Integration with public health initiatives, lifestyle interventions, and conventional screening programs ensures a multi-layered preventive framework. By leveraging precision immunology and vaccine technology, personalized immunoprevention represents a paradigm shift toward proactive cancer interception, offering the potential to significantly reduce incidence and improve population health outcomes.

Pharmacologic and chemopreventive interventions play a crucial role in reducing cancer risk, particularly for individuals at high genetic, molecular, or environmental susceptibility. This session explores the evidence-based use of drugs and biologics to prevent the initiation, progression, or recurrence of malignancies, integrating molecular profiling, risk stratification, and clinical guidelines. Agents such as selective estrogen receptor modulators (SERMs), aromatase inhibitors, nonsteroidal anti-inflammatory drugs (NSAIDs), and metformin are discussed for their chemopreventive properties in breast, colorectal, and other cancers. Mechanisms of action, including modulation of hormonal pathways, inhibition of inflammatory cascades, suppression of cell proliferation, and induction of apoptosis, are examined to understand how pharmacologic interventions target early carcinogenic processes. The session emphasizes patient selection using biomarkers, genetic testing, and risk models to optimize efficacy and minimize adverse effects. Clinical trial evidence, including randomized controlled studies and long-term follow-up data, is reviewed to guide decision-making in preventive therapy. Safety monitoring, dose optimization, adherence support, and management of side effects are critical components of effective chemoprevention programs. Integration with lifestyle interventions, immunopreventive strategies, and routine screening enhances overall cancer risk reduction. Ethical considerations, including informed consent, patient autonomy, and equitable access, underpin the use of pharmacologic preventive measures. Emerging areas such as targeted small molecules, epigenetic modifiers, and combination preventive regimens are highlighted for their potential to expand personalized prevention. By combining molecular insights, clinical evidence, and individualized risk assessment, pharmacologic and chemopreventive strategies provide a proactive approach to cancer prevention, reducing incidence and improving long-term outcomes while complementing screening, immunoprevention, and lifestyle-based interventions.

Digital health technologies and tele-oncology are revolutionizing the delivery of preventive oncology services, extending early detection, risk assessment, and patient education beyond traditional healthcare settings. Mobile health applications, wearable biosensors, and remote monitoring devices enable continuous tracking of health metrics, lifestyle factors, and early warning signs associated with cancer risk. Integration of telemedicine platforms allows virtual consultations, genetic counseling, and follow-up care, overcoming geographic and socioeconomic barriers to access. Artificial intelligence-driven decision-support tools embedded in digital platforms provide real-time risk stratification, recommend personalized screening schedules, and facilitate timely intervention. Data from electronic health records, population registries, and patient-generated health data can be aggregated and analyzed to identify trends, improve preventive strategies, and support research initiatives. The session highlights the role of predictive modeling, machine learning, and cloud-based analytics in optimizing early detection pathways, enhancing clinical workflow, and improving resource allocation. Challenges such as data security, patient privacy, interoperability, and equitable access are addressed, along with strategies to mitigate digital health disparities. Digital literacy programs, culturally tailored user interfaces, and community engagement are critical to maximizing adoption and effectiveness. By integrating digital health solutions with conventional clinical care, preventive oncology can become more proactive, patient-centered, and scalable. These technologies not only enhance early cancer detection but also empower patients with tools to monitor and modify their risk factors, creating a comprehensive and sustainable framework for preventive care at both individual and population levels.

The future of preventive oncology lies in integrating technological innovation, precision medicine, and systems-level approaches to dramatically reduce cancer incidence and mortality. Emerging trends include multi-omics profiling, artificial intelligence, predictive analytics, and immunoprevention strategies that allow earlier identification and interception of malignancy. Personalized prevention pathways will increasingly combine genetic, molecular, environmental, and lifestyle data to guide individualized interventions and optimize screening schedules. Novel diagnostic tools such as liquid biopsies, advanced imaging modalities, and real-time wearable biosensors will facilitate continuous risk monitoring and adaptive preventive strategies. Integration of behavioral science, community engagement, and public health policy ensures that innovations are effectively implemented at population scale and reach underserved communities. Ethical considerations, regulatory compliance, and equitable access will remain central to responsible deployment, ensuring that benefits are widely shared and harm is minimized. Collaborative global research networks, translational pipelines, and multi-center clinical trials accelerate the adoption of innovative preventive interventions. The session also explores cost-effectiveness modeling, sustainability frameworks, and health systems integration to ensure that innovations are scalable and deliver measurable outcomes. By combining cutting-edge science, digital health, precision medicine, and public health infrastructure, the future of preventive oncology promises a paradigm shift from reactive treatment to proactive, personalized cancer prevention, ultimately improving survival rates and quality of life worldwide.

Integrating psychosocial considerations into preventive oncology is essential for improving patient engagement, adherence, and overall outcomes. Psychological factors such as anxiety, perceived risk, health beliefs, and social support influence individuals’ participation in screening programs, adherence to preventive therapies, and responsiveness to lifestyle interventions. Understanding these behavioral determinants allows clinicians and public health professionals to design personalized, patient-centered strategies that encourage proactive participation in cancer prevention initiatives. Interventions include structured counseling, motivational interviewing, cognitive-behavioral approaches, and peer-support networks aimed at enhancing health literacy and informed decision-making. The session examines strategies for managing distress related to genetic testing, biomarker results, or incidental findings from multi-modal screening, emphasizing ethical communication, shared decision-making, and informed consent. Socioeconomic and cultural factors that contribute to disparities in preventive oncology uptake are addressed, with a focus on tailoring interventions for diverse populations and underserved communities. Technology-assisted psychosocial support, including tele-counseling, mobile apps, and digital communities, is increasingly being used to extend access to mental health and educational resources in real-time. The integration of psychosocial assessment tools into clinical workflows enables continuous monitoring of patient well-being and adherence, facilitating adaptive interventions. By combining behavioral science, community engagement, and patient-centered care models, this session highlights how preventive oncology can move beyond technical diagnostics to address the holistic needs of patients, improve participation in early detection programs, and ultimately enhance long-term health outcomes and quality of life.

Diet, physical activity, and lifestyle factors are central components of cancer prevention, and targeted interventions can significantly reduce both cancer incidence and progression risk. This session examines evidence-based strategies for dietary modification, including the promotion of plant-based foods, reduction of processed and red meats, moderation of alcohol intake, and maintenance of healthy body weight. Nutritional interventions are linked to the modulation of metabolic pathways, inflammation, hormonal regulation, and gut microbiome composition, all of which influence oncogenesis. Physical activity, encompassing aerobic, resistance, and flexibility exercises, is discussed for its role in reducing cancer risk through improved immune function, regulation of insulin and growth factors, and weight management. Behavioral modification strategies, including goal setting, self-monitoring, motivational interviewing, and structured coaching, support sustained adoption of healthy lifestyles. The session emphasizes culturally sensitive approaches that account for socioeconomic, ethnic, and geographic differences in diet, access to exercise facilities, and health literacy. Community-based programs, school- and workplace-focused interventions, and digital platforms such as mobile apps and wearable trackers are explored as scalable tools to support population-level lifestyle modification. In addition, the session addresses the challenges of adherence, evaluation of program effectiveness, and integration of lifestyle counseling into routine preventive oncology practice. Collaboration between clinicians, dietitians, behavioral scientists, and public health professionals is emphasized to create multi-disciplinary interventions that are both evidence-based and patient-centered. By combining nutritional guidance, physical activity promotion, and behavioral science, lifestyle interventions become a cornerstone of comprehensive cancer prevention strategies, complementing molecular diagnostics, screening, and immunoprevention approaches. This integrated approach not only reduces cancer risk but also improves overall health, quality of life, and long-term wellness outcomes at both the individual and population level.

Exposure to environmental and occupational carcinogens is a major contributor to cancer incidence worldwide, and targeted prevention strategies are critical for reducing risk. This session examines the identification, monitoring, and mitigation of chemical, physical, and biological carcinogens in workplaces, homes, and communities. Key exposures include asbestos, benzene, polycyclic aromatic hydrocarbons, formaldehyde, heavy metals, ionizing radiation, and certain pesticides, as well as indoor and outdoor air pollution. Participants will explore methods for risk assessment, including biomonitoring, exposure modeling, and epidemiological surveillance, which inform evidence-based regulatory standards and occupational safety protocols. Strategies for prevention encompass policy interventions, such as workplace safety regulations, emission controls, and environmental remediation programs, alongside individual-level measures like personal protective equipment, lifestyle modifications, and education campaigns. The session emphasizes the importance of integrating environmental risk assessment into national cancer prevention frameworks and clinical risk stratification models. Multidisciplinary collaboration between occupational health specialists, industrial hygienists, public health authorities, and policymakers is critical to ensure effective implementation and enforcement. Digital tools and geographic information systems (GIS) are increasingly used to map exposure patterns, track high-risk populations, and design targeted interventions. Special attention is given to vulnerable populations, including children, pregnant women, and low-income communities disproportionately affected by environmental hazards. Ethical, legal, and socioeconomic considerations underpin the development and implementation of preventive strategies, ensuring that interventions are equitable, sustainable, and culturally appropriate. By combining environmental science, occupational health, regulatory policy, and public health practice, this session highlights comprehensive approaches to reducing carcinogen exposure, preventing environmentally induced cancers, and promoting safer workplaces and communities.

Effective cancer prevention relies not only on the development of advanced diagnostics and interventions but also on the systematic implementation and evaluation of these strategies in real-world settings. This session focuses on implementation science, which studies the methods and processes that ensure evidence-based preventive oncology practices are adopted, integrated, and sustained across diverse healthcare systems and populations. Participants will examine frameworks for translating research into practice, including the identification of barriers and facilitators at individual, organizational, and policy levels. Key topics include fidelity of intervention delivery, adaptation to local contexts, stakeholder engagement, and integration with existing healthcare infrastructures. Monitoring and evaluation strategies are emphasized to assess both process and outcome metrics, such as screening uptake, adherence to preventive interventions, reduction in cancer incidence, and patient-reported outcomes. Real-world data sources, including electronic health records, cancer registries, mobile health applications, and population surveys, are leveraged to measure effectiveness and inform continuous quality improvement. Cost-effectiveness analysis, health economics modeling, and sustainability planning are incorporated to ensure interventions are scalable and resource-efficient. Special attention is given to equity considerations, addressing disparities in access, engagement, and outcomes among socioeconomically and geographically diverse populations. Collaborative approaches, involving clinicians, public health professionals, policymakers, and community stakeholders, are highlighted as essential to successful implementation. By combining rigorous evaluation, adaptive strategies, and evidence-based planning, implementation science ensures that innovations in preventive oncology translate into meaningful population health benefits. This approach closes the loop from discovery to impact, ensuring that advances in screening, diagnostics, lifestyle interventions, immunoprevention, and digital health are effectively delivered, monitored, and refined to achieve sustainable reductions in cancer burden worldwide.

Ensuring equitable access to preventive oncology services is critical for reducing disparities in cancer incidence and outcomes across populations. This session focuses on identifying and addressing systemic, socioeconomic, cultural, and geographic barriers that limit access to screening, early detection, lifestyle interventions, and immunoprevention strategies. Participants will explore strategies for improving health literacy, culturally tailored education programs, and community engagement initiatives designed to empower patients to participate actively in preventive care. Special attention is given to vulnerable populations, including low-income communities, rural residents, racial and ethnic minorities, and individuals with limited digital access. Policy interventions, such as subsidized screening programs, insurance coverage for preventive services, and public health campaigns, are examined as mechanisms to promote equitable access. Integration of digital health tools, telemedicine, and mobile health platforms allows remote populations to receive counseling, monitoring, and follow-up care, bridging gaps in service delivery. The session also emphasizes the role of stakeholder collaboration, involving healthcare providers, community organizations, policymakers, and patient advocates, to design and implement inclusive programs. Metrics and monitoring systems are discussed for evaluating the impact of equity-focused interventions on participation rates, early detection, and long-term cancer outcomes. Ethical considerations, including fairness, resource allocation, and respect for patient autonomy, underpin all strategies for promoting access. By combining public health policy, community-based approaches, digital solutions, and culturally informed practices, this session highlights pathways to achieve health equity in preventive oncology, ensuring that advances in early detection, lifestyle interventions, and immunoprevention benefit all populations, regardless of social or geographic constraints.

The integration of genomic data into preventive oncology enables highly personalized risk assessment, early detection, and tailored intervention strategies. This session explores the use of germline and somatic genomic information, polygenic risk scores, and multi-omics datasets to stratify individuals according to cancer susceptibility and inform precision prevention programs. Participants will examine how next-generation sequencing, whole-exome sequencing, and genome-wide association studies provide comprehensive insights into hereditary cancer syndromes, moderate-risk variants, and emerging susceptibility loci. Integration with transcriptomic, proteomic, and epigenetic data allows for dynamic modeling of disease risk and prediction of tumor progression trajectories. Advanced computational tools, including machine learning and predictive algorithms, enable the construction of individualized risk models that combine genetic, environmental, lifestyle, and demographic factors. These models support personalized screening schedules, early intervention strategies, and targeted preventive therapies. Ethical and regulatory considerations, including data privacy, informed consent, and equitable access, are emphasized to ensure responsible use of genomic information. Clinical workflows integrating genomic risk assessment with preventive care protocols are discussed, highlighting the role of genetic counseling, patient education, and shared decision-making. Challenges related to data standardization, interoperability, and interpretation of variants of uncertain significance are addressed, along with strategies to enhance accuracy and clinical utility. By leveraging genomic integration and precision risk modeling, preventive oncology can move beyond population-level screening toward highly individualized strategies that optimize early detection, reduce overdiagnosis, and improve long-term outcomes. This approach represents a key pillar of modern cancer prevention, bridging the gap between molecular science and actionable clinical practice.

Advanced imaging technologies, combined with radiomics and computational analysis, are transforming the early detection of cancer by extracting detailed quantitative information from medical images that goes beyond conventional interpretation. This session explores how modalities such as low-dose computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and hybrid imaging systems can identify subtle morphological, functional, and metabolic changes indicative of early malignancy. Radiomics leverages high-dimensional data extracted from imaging—such as texture, shape, intensity, and spatial relationships—to uncover patterns that correlate with tumor biology, genetic alterations, and clinical outcomes. Machine learning and artificial intelligence algorithms enhance the ability to detect small lesions, differentiate benign from malignant findings, and predict tumor aggressiveness, improving both sensitivity and specificity in screening programs. Integration with multi-omics datasets, including genomics and proteomics, facilitates comprehensive risk assessment and individualized diagnostic pathways. The session also highlights the role of image-guided biopsy, interventional radiology, and longitudinal imaging for monitoring precancerous lesions and treatment response. Quality assurance, standardization of imaging protocols, reproducibility of radiomic features, and validation in multi-center studies are emphasized to ensure clinical utility. Ethical considerations, including patient consent, radiation exposure, incidental findings, and equitable access to advanced imaging, are addressed as part of responsible implementation. Challenges such as data storage, interoperability with electronic health records, and the need for trained multidisciplinary teams are discussed alongside potential solutions. By combining cutting-edge imaging technology with computational analysis, radiomics provides a powerful tool for early cancer detection, enabling personalized surveillance, minimizing invasive procedures, and supporting proactive preventive oncology strategies that improve patient outcomes and optimize healthcare resources.