{"title":"Current AI technologies in cancer diagnostics and treatment","authors":"Ashutosh Tiwari, Soumya Mishra, Tsung-Rong Kuo","doi":"10.1186/s12943-025-02369-9","DOIUrl":null,"url":null,"abstract":"Cancer continues to be a significant international health issue, which demands the invention of new methods for early detection, precise diagnoses, and personalized treatments. Artificial intelligence (AI) has rapidly become a groundbreaking component in the modern era of oncology, offering sophisticated tools across the range of cancer care. In this review, we performed a systematic survey of the current status of AI technologies used for cancer diagnoses and therapeutic approaches. We discuss AI-facilitated imaging diagnostics using a range of modalities such as computed tomography, magnetic resonance imaging, positron emission tomography, ultrasound, and digital pathology, highlighting the growing role of deep learning in detecting early-stage cancers. We also explore applications of AI in genomics and biomarker discovery, liquid biopsies, and non-invasive diagnoses. In therapeutic interventions, AI-based clinical decision support systems, individualized treatment planning, and AI-facilitated drug discovery are transforming precision cancer therapies. The review also evaluates the effects of AI on radiation therapy, robotic surgery, and patient management, including survival predictions, remote monitoring, and AI-facilitated clinical trials. Finally, we discuss important challenges such as data privacy, interpretability, and regulatory issues, and recommend future directions that involve the use of federated learning, synthetic biology, and quantum-boosted AI. This review highlights the groundbreaking potential of AI to revolutionize cancer care by making diagnostics, treatments, and patient management more precise, efficient, and personalized. This graphical abstract schematically illustrates the progressive role of artificial intelligence in the cancer treatment continuum. ","PeriodicalId":19000,"journal":{"name":"Molecular Cancer","volume":"7 1","pages":""},"PeriodicalIF":27.7000,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Cancer","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12943-025-02369-9","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Cancer continues to be a significant international health issue, which demands the invention of new methods for early detection, precise diagnoses, and personalized treatments. Artificial intelligence (AI) has rapidly become a groundbreaking component in the modern era of oncology, offering sophisticated tools across the range of cancer care. In this review, we performed a systematic survey of the current status of AI technologies used for cancer diagnoses and therapeutic approaches. We discuss AI-facilitated imaging diagnostics using a range of modalities such as computed tomography, magnetic resonance imaging, positron emission tomography, ultrasound, and digital pathology, highlighting the growing role of deep learning in detecting early-stage cancers. We also explore applications of AI in genomics and biomarker discovery, liquid biopsies, and non-invasive diagnoses. In therapeutic interventions, AI-based clinical decision support systems, individualized treatment planning, and AI-facilitated drug discovery are transforming precision cancer therapies. The review also evaluates the effects of AI on radiation therapy, robotic surgery, and patient management, including survival predictions, remote monitoring, and AI-facilitated clinical trials. Finally, we discuss important challenges such as data privacy, interpretability, and regulatory issues, and recommend future directions that involve the use of federated learning, synthetic biology, and quantum-boosted AI. This review highlights the groundbreaking potential of AI to revolutionize cancer care by making diagnostics, treatments, and patient management more precise, efficient, and personalized. This graphical abstract schematically illustrates the progressive role of artificial intelligence in the cancer treatment continuum.
期刊介绍:
Molecular Cancer is a platform that encourages the exchange of ideas and discoveries in the field of cancer research, particularly focusing on the molecular aspects. Our goal is to facilitate discussions and provide insights into various areas of cancer and related biomedical science. We welcome articles from basic, translational, and clinical research that contribute to the advancement of understanding, prevention, diagnosis, and treatment of cancer.
The scope of topics covered in Molecular Cancer is diverse and inclusive. These include, but are not limited to, cell and tumor biology, angiogenesis, utilizing animal models, understanding metastasis, exploring cancer antigens and the immune response, investigating cellular signaling and molecular biology, examining epidemiology, genetic and molecular profiling of cancer, identifying molecular targets, studying cancer stem cells, exploring DNA damage and repair mechanisms, analyzing cell cycle regulation, investigating apoptosis, exploring molecular virology, and evaluating vaccine and antibody-based cancer therapies.
Molecular Cancer serves as an important platform for sharing exciting discoveries in cancer-related research. It offers an unparalleled opportunity to communicate information to both specialists and the general public. The online presence of Molecular Cancer enables immediate publication of accepted articles and facilitates the presentation of large datasets and supplementary information. This ensures that new research is efficiently and rapidly disseminated to the scientific community.