Artificial Intelligence for Future Healthcare: Advancement, Impact, and Prospect in the Field of Cancer
A special issue of AI (ISSN 2673-2688). This special issue belongs to the section "Medical & Healthcare AI".
Deadline for manuscript submissions: 31 December 2025 | Viewed by 801
Special Issue Editor
Interests: artificial intelligence for workflow optimization and risk prediction; quantitative imaging; blood perfusion quantification; cancer screening devices, and hyperthermia-based cancer treatment strategies
Special Issue Information
Dear Colleagues,
Artificial intelligence (AI) for future healthcare is a specialized topic which aims to cover current or past AI developments, as well as its potential impact and future prospects in cancer management. With the advent of deep learning, the application of AI in healthcare has grown significantly over the years; nevertheless, many of these current applications are task-specific or rigid to certain sets of input data. This has frequently limited the ability of deep learning tools to diverse and distinct data sources. Consequently, the focus going forward should be the development of generalized medical AI systems that can process and interpret multimodal data—such as images from various scans, laboratory results, blood-borne markers, wearable signals, microbiomes, and omics, as well as many inputs, such as unstructured or structured medical text, voice, and images. In this direction, generative AI and transformers could be vital technologies wherein a blended stream of diverse data tokens can be fed.
This research topic on the advancement, impact, and prospects of AI in the field of cancer holds great promise for revolutionizing healthcare delivery, enabling personalized medicine, democratizing technologies, and improving patient outcomes across diverse clinical applications. As research in this field continues to evolve, we can expect to see further innovations that will shape the future of AI in healthcare. The purpose of this research topic is to bring together new developments and advances within this field, providing valuable insights in current and future prospects of AI in healthcare specific to the field of cancer management. This research topic also welcomes literature reviews and work on focused areas such as AI explainability, bias mitigation, generalizability, futuristic applications, multi-modal aspects, and the validation of AI tools.
Manuscripts focused on the following areas are of particular interest to this research topic:
- Recent developments in multi-modal AI for cancer screening, diagnosis, prognosis, risk prediction, and longitudinal risk monitoring;
- Recent advances in AI for cancer treatment planning, preventative therapy, prediction of drug effectiveness, and digital drug development;
- Innovative and futuristic AI tools for patient triage, workflow optimization, and diagnostic and treatment assistance to augmented procedures (e.g., image-to-text generation and image-to-voice generation for scoping or surgical procedure);
- AI for predicting cancer patterns and risks from image biomarkers, wearable data, laboratory data, omics data, and microbiome data;
- AI as a virtual health coach, AI to improve patient–doctor relationships, and AI to mitigate diagnostic errors;
- AI for remote monitoring, home care, integration with teleconsultation, and affordable technologies for low-resource settings.
Dr. Arka Bhowmik
Guest Editor
Manuscript Submission Information
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Keywords
- AI for cancer forecasting
- multi-modal AI
- high-risk prediction
- risk monitoring
- preventive therapy
- democratized AI technology
- augmented procedures
- doctor–patient relationship
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