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Artificial Intelligence and cancer: Profile of registered clinical trials.

Journal of cancer policy
Artificial Intelligence (AI) has made significant strides due to advancements in processing algorithms and data availability. Recent years have shown a resurgence in AI, driven by breakthroughs in deep machine learning. AI has attracted particular in...

A Contrastive-Learning-Based Deep Neural Network for Cancer Subtyping by Integrating Multi-Omics Data.

Interdisciplinary sciences, computational life sciences
BACKGROUND: Accurate identification of cancer subtypes is crucial for disease prognosis evaluation and personalized patient management. Recent advances in computational methods have demonstrated that multi-omics data provides valuable insights into t...

Generative AI in oncological imaging: Revolutionizing cancer detection and diagnosis.

Oncotarget
Generative AI is revolutionizing oncological imaging, enhancing cancer detection and diagnosis. This editorial explores its impact on expanding datasets, improving image quality, and enabling predictive oncology. We discuss ethical considerations and...

Machine Learning for Targeted Advance Care Planning in Cancer Patients: A Quality Improvement Study.

Journal of pain and symptom management
CONTEXT: Prognostication challenges contribute to delays in advance care planning (ACP) for patients with cancer near the end of life (EOL).

The scienthetic method: from Aristotle to AI and the future of medicine.

British journal of cancer
While AI holds immense potential for accelerating advances in oncology, we must be intentional in developing and applying these technologies responsibly, equitably, and ethically. One path forward is for cancer care providers and researchers to be am...

An Explainable Graph Neural Framework to Identify Cancer-Associated Intratumoral Microbial Communities.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Microbes are extensively present among various cancer tissues and play critical roles in carcinogenesis and treatment responses. However, the underlying relationships between intratumoral microbes and tumors remain poorly understood. Here, a MIcrobia...

Machine learning to identify precachexia and cachexia: a multicenter, retrospective cohort study.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
BACKGROUND: Detection of precachexia is important for the prevention and treatment of cachexia. However, how to identify precachexia is still a challenge.

The emerging role of Artificial Intelligence in proton therapy: A review.

Critical reviews in oncology/hematology
Artificial intelligence (AI) has made a tremendous impact in the space of healthcare, and proton therapy is not an exception. Proton therapy has witnessed growing popularity in oncology over recent decades, and researchers are increasingly looking to...

ConvNext Mitosis Identification-You Only Look Once (CNMI-YOLO): Domain Adaptive and Robust Mitosis Identification in Digital Pathology.

Laboratory investigation; a journal of technical methods and pathology
In digital pathology, accurate mitosis detection in histopathological images is critical for cancer diagnosis and prognosis. However, this remains challenging due to the inherent variability in cell morphology and the domain shift problem. This study...

Magnetic Resonance-Guided Cancer Therapy Radiomics and Machine Learning Models for Response Prediction.

Tomography (Ann Arbor, Mich.)
Magnetic resonance imaging (MRI) is known for its accurate soft tissue delineation of tumors and normal tissues. This development has significantly impacted the imaging and treatment of cancers. Radiomics is the process of extracting high-dimensional...