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Synthetic augmentation of cancer cell line multi-omic datasets using unsupervised deep learning.

Nature communications
Integrating diverse types of biological data is essential for a holistic understanding of cancer biology, yet it remains challenging due to data heterogeneity, complexity, and sparsity. Addressing this, our study introduces an unsupervised deep learn...

The role of artificial intelligence in immune checkpoint inhibitor research: A bibliometric analysis.

Human vaccines & immunotherapeutics
Immune checkpoint inhibitors (ICIs) are revolutionizing cancer treatment, and Artificial Intelligence (AI) is a key player in this field. A comprehensive analysis of AI's impact on these inhibitors was lacking, but this study addresses that by analyz...

Metastatic Versus Localized Disease as Inclusion Criteria That Can Be Automatically Extracted From Randomized Controlled Trials Using Natural Language Processing.

JCO clinical cancer informatics
PURPOSE: Extracting inclusion and exclusion criteria in a structured, automated fashion remains a challenge to developing better search functionalities or automating systematic reviews of randomized controlled trials in oncology. The question "Did th...

GFPrint™: A machine learning tool for transforming genetic data into clinical insights.

PloS one
The increasing availability of massive genetic sequencing data in the clinical setting has triggered the need for appropriate tools to help fully exploit the wealth of information these data possess. GFPrint™ is a proprietary streaming algorithm desi...

Targeted isolation and AI-based analysis of edible fungal polysaccharides: Emphasizing tumor immunological mechanisms and future prospects as mycomedicines.

International journal of biological macromolecules
Edible fungal polysaccharides have emerged as significant bioactive compounds with diverse therapeutic potentials, including notable anti-tumor effects. Derived from various fungal sources, these polysaccharides exhibit complex biological activities ...

SLInterpreter: An Exploratory and Iterative Human-AI Collaborative System for GNN-Based Synthetic Lethal Prediction.

IEEE transactions on visualization and computer graphics
Synthetic Lethal (SL) relationships, though rare among the vast array of gene combinations, hold substantial promise for targeted cancer therapy. Despite advancements in AI model accuracy, there is still a significant need among domain experts for in...

A machine learning-based analysis of nationwide cancer comprehensive genomic profiling data across cancer types to identify features associated with recommendation of genome-matched therapy.

ESMO open
BACKGROUND: The low probability of identifying druggable mutations through comprehensive genomic profiling (CGP) and its financial and time costs hinder its widespread adoption. To enhance the effectiveness and efficiency of cancer precision medicine...

Large Language Models to Identify Advance Care Planning in Patients With Advanced Cancer.

Journal of pain and symptom management
CONTEXT: Efficiently tracking Advance Care Planning (ACP) documentation in electronic heath records (EHRs) is essential for quality improvement and research efforts. The use of large language models (LLMs) offers a novel approach to this task.

Factors inducing cutaneous adverse reactions in cancer patients treated with PD-1 and PD-L1 inhibitors: a machine-learning algorithm approach.

Immunopharmacology and immunotoxicology
BACKGROUND: Immune checkpoint inhibitors (ICIs) show promise in cancer treatment but can lead to immune-related adverse events (irAEs), notably affecting the skin. Understanding the factors behind these skin reactions is crucial for effective managem...

Automated robotic-assisted patient positioning method and dosimetric impact analysis for boron neutron capture therapy.

Scientific reports
Boron Neutron Capture Therapy (BNCT) represents a revolutionary approach in targeted radiation treatment for cancer. While the therapy's potential in precise targeting is well-recognized, a critical bottleneck remains in the accurate positioning of p...