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Neoplasms

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MCMVDRP: a multi-channel multi-view deep learning framework for cancer drug response prediction.

Journal of integrative bioinformatics
Drug therapy remains the primary approach to treating tumours. Variability among cancer patients, including variations in genomic profiles, often results in divergent therapeutic responses to analogous anti-cancer drug treatments within the same coho...

Artificial intelligence for response prediction and personalisation in radiation oncology.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Artificial intelligence (AI) systems may personalise radiotherapy by assessing complex and multifaceted patient data and predicting tumour and normal tissue responses to radiotherapy. Here we describe three distinct generations of AI systems, namely ...

Advances in exosome plasmonic sensing: Device integration strategies and AI-aided diagnosis.

Biosensors & bioelectronics
Exosomes, as next-generation biomarkers, has great potential in tracking cancer progression. They face many detection limitations in cancer diagnosis. Plasmonic biosensors have attracted considerable attention at the forefront of exosome detection, d...

The role of artificial intelligence in the development of anticancer therapeutics from natural polyphenols: Current advances and future prospects.

Pharmacological research
Natural polyphenols, abundant in the human diet, are derived from a wide variety of sources. Numerous preclinical studies have demonstrated their significant anticancer properties against various malignancies, making them valuable resources for drug ...

Artificial intelligence: illuminating the depths of the tumor microenvironment.

Journal of translational medicine
Artificial intelligence (AI) can acquire characteristics that are not yet known to humans through extensive learning, enabling to handle large amounts of pathology image data. Divided into machine learning and deep learning, AI has the advantage of h...

Artificial intelligence-based motion tracking in cancer radiotherapy: A review.

Journal of applied clinical medical physics
Radiotherapy aims to deliver a prescribed dose to the tumor while sparing neighboring organs at risk (OARs). Increasingly complex treatment techniques such as volumetric modulated arc therapy (VMAT), stereotactic radiosurgery (SRS), stereotactic body...

Multitask Learning on Graph Convolutional Residual Neural Networks for Screening of Multitarget Anticancer Compounds.

Journal of chemical information and modeling
Recently, various modern experimental screening pipelines and assays have been developed to find promising anticancer drug candidates. However, it is time-consuming and almost infeasible to screen an immense number of compounds for anticancer activit...

Developing a low-cost, open-source, locally manufactured workstation and computational pipeline for automated histopathology evaluation using deep learning.

EBioMedicine
BACKGROUND: Deployment and access to state-of-the-art precision medicine technologies remains a fundamental challenge in providing equitable global cancer care in low-resource settings. The expansion of digital pathology in recent years and its poten...

The Role of Artificial Intelligence on Tumor Boards: Perspectives from Surgeons, Medical Oncologists and Radiation Oncologists.

Current oncology (Toronto, Ont.)
The integration of multidisciplinary tumor boards (MTBs) is fundamental in delivering state-of-the-art cancer treatment, facilitating collaborative diagnosis and management by a diverse team of specialists. Despite the clear benefits in personalized ...