The adoption of artificial intelligence (AI) tools in medicine poses challenges to existing
clinical workflows. This commentary discusses the necessity of context-specific quality …

Abstract Artificial Intelligence (AI) and Deep Learning have emerged as revolutionary tools
in the domain of cancer screening and risk assessment. Leveraging vast amounts of data …

Opinion statement Treatment guidelines for colorectal cancer (CRC) are primarily based on
the results of randomized clinical trials (RCTs), the gold standard methodology to evaluate …

Tumor heterogeneity is a primary factor that contributes to treatment failure. Predictive tools,
capable of classifying cancer cells based on their functions, may substantially enhance …

With the rapid progress of information technology and life sciences, artificial intelligence (AI)
technology has substantially changed the way in many areas of biomaterials and …

Context For some common thyroid-related conditions with high prevalence and long follow-
up times, ChatGPT can be used to respond to common thyroid-related questions. Objective …

Drug resistance in cancer treatment presents a significant challenge, necessitating
innovative approaches to improve therapeutic efficacy. Integrating machine learning (ML) in …

Drug repurposing is the strategy of drug utilization for a treatment option other than the
intended indications and has increased over the past decades, especially within cancer …

Purpose Artificial intelligence (AI) based commercial software can be used to automatically
delineate organs at risk (OAR), with potential for efficiency savings in the radiotherapy …

AI-driven precision oncology has the transformative potential to reshape cancer treatment by
leveraging the power of AI models to analyze the interaction between complex patient …