AIMC Topic: Neoplasms

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Optimizing thermal dose prediction in nanoparticle-mediated photothermal therapy using a convolutional neural network-based model.

Journal of thermal biology
Nanoparticle-mediated photothermal therapy (NMPTT) is an up-and-coming targeted cancer treatment. Here, nanoparticles are used to convert near-infrared light into localized heat that can kill tumour cells while sparing surrounding healthy tissue. Nev...

Explainable AI-driven prediction of APE1 inhibitors: enhancing cancer therapy with machine learning models and feature importance analysis.

Molecular diversity
The viability of cells and the integrity of the genome depend on the detection and repair of damaged DNA through intricate mechanisms. Cancer treatment employs chemotherapy or radiation therapy to eliminate neoplastic cells by causing substantial dam...

Multi-cancer early detection based on serum surface-enhanced Raman spectroscopy with deep learning: a large-scale case-control study.

BMC medicine
BACKGROUND: Early detection of cancer can help patients with more effective treatments and result in better prognosis. Unfortunately, established cancer screening technologies are limited for use, especially for multi-cancer early detection. In this ...

Externally validated and clinically useful machine learning algorithms to support patient-related decision-making in oncology: a scoping review.

BMC medical research methodology
BACKGROUND: This scoping review systematically maps externally validated machine learning (ML)-based models in cancer patient care, quantifying their performance, and clinical utility, and examining relationships between models, cancer types, and cli...

Intuitive Human-Artificial Intelligence Theranostic Complementarity.

Cancer biotherapy & radiopharmaceuticals
Deep learning artificial intelligence (AI) algorithms are poised to subsume diagnostic imaging specialists in radiology and nuclear medicine, where radiomics can consistently outperform human analysis and reporting capability, and do it faster, with ...

Radiomics and Deep Learning Prediction of Immunotherapy-Induced Pneumonitis From Computed Tomography.

JCO clinical cancer informatics
PURPOSE: Primary barriers to application of immune checkpoint inhibitor (ICI) therapy for cancer include severe side effects (such as potentially life threatening pneumonitis [PN]), which can cause the discontinuation of treatment. Predicting which p...

Using mathematical modelling and AI to improve delivery and efficacy of therapies in cancer.

Nature reviews. Cancer
Mathematical modelling has proven to be a valuable tool in predicting the delivery and efficacy of molecular, antibody-based, nano and cellular therapy in solid tumours. Mathematical models based on our understanding of the biological processes at su...

Artificial Intelligence Applications in Cardio-Oncology: A Comprehensive Review.

Current cardiology reports
PURPOSE OF REVIEW: This review explores the role of artificial intelligence (AI) in cardio-oncology, focusing on its latest application across problems in diagnosis, prognosis, risk stratification, and management of cardiovascular (CV) complications ...

Evidence-Based Analysis of AI Chatbots in Oncology Patient Education: Implications for Trust, Perceived Realness, and Misinformation Management.

Journal of cancer education : the official journal of the American Association for Cancer Education
The rapid integration of AI-driven chatbots into oncology education represents both a transformative opportunity and a critical challenge. These systems, powered by advanced language models, can deliver personalized, real-time cancer information to p...

Radiation oncology at crossroads: Rise of AI and managing the unexpected.

Journal of applied clinical medical physics
Integrating artificial intelligence (AI) into radiation oncology has revolutionized clinical workflows, enhancing efficiency, safety, and quality. However, this transformation comes with a price of increased complexity and the emergence of unpredicta...