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Machine Learning Methods for Precision Dosing in Anticancer Drug Therapy: A Scoping Review.

Clinical pharmacokinetics
INTRODUCTION: In the last decade, various Machine Learning techniques have been proposed aiming to individualise the dose of anticancer drugs mostly based on a presumed drug effect or measured effect biomarkers. The aim of this scoping review was to ...

Chemical analogue based drug design for cancer treatment targeting PI3K: integrating machine learning and molecular modeling.

Molecular diversity
Cancer is a generic term for a group of disorders defined by uncontrolled cell growth and the potential to invade or spread to other parts of the body. Gene and epigenetic alterations disrupt normal cellular control, leading to abnormal cell prolifer...

Predicting tissue distribution and tumor delivery of nanoparticles in mice using machine learning models.

Journal of controlled release : official journal of the Controlled Release Society
Nanoparticles (NPs) can be designed for targeted delivery in cancer nanomedicine, but the challenge is a low delivery efficiency (DE) to the tumor site. Understanding the impact of NPs' physicochemical properties on target tissue distribution and tum...

Enhancing targeted tumor treatment: A novel fuzzy logic framework for precision drug delivery strategy selection.

Computers in biology and medicine
OBJECTIVE: This study aims to address the challenge of selecting optimal drug delivery strategies for tumor patients by introducing a novel theoretical framework.

Hybridizing mechanistic modeling and deep learning for personalized survival prediction after immune checkpoint inhibitor immunotherapy.

NPJ systems biology and applications
We present a study where predictive mechanistic modeling is combined with deep learning methods to predict individual patient survival probabilities under immune checkpoint inhibitor (ICI) immunotherapy. This hybrid approach enables prediction based ...

Cancer Prevention and Treatment on Chinese Social Media: Machine Learning-Based Content Analysis Study.

Journal of medical Internet research
BACKGROUND: Nowadays, social media plays a crucial role in disseminating information about cancer prevention and treatment. A growing body of research has focused on assessing access and communication effects of cancer information on social media. Ho...

Revolutionizing adjuvant development: harnessing AI for next-generation cancer vaccines.

Frontiers in immunology
With the COVID-19 pandemic, the importance of vaccines has been widely recognized and has led to increased research and development efforts. Vaccines also play a crucial role in cancer treatment by activating the immune system to target and destroy c...

Artificial intelligence for treatment delivery: image-guided radiotherapy.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Radiation therapy (RT) is a highly digitized field relying heavily on computational methods and, as such, has a high affinity for the automation potential afforded by modern artificial intelligence (AI). This is particularly relevant where imaging is...

Artificial Intelligence for Radiation Treatment Planning: Bridging Gaps From Retrospective Promise to Clinical Reality.

Clinical oncology (Royal College of Radiologists (Great Britain))
Artificial intelligence (AI) radiation therapy (RT) planning holds promise for enhancing the consistency and efficiency of the RT planning process. Despite technical advancements, the widespread integration of AI into RT treatment planning faces chal...

End-to-end reproducible AI pipelines in radiology using the cloud.

Nature communications
Artificial intelligence (AI) algorithms hold the potential to revolutionize radiology. However, a significant portion of the published literature lacks transparency and reproducibility, which hampers sustained progress toward clinical translation. Al...