Core Insights - Artificial Intelligence (AI) is rapidly becoming an essential technology in the field of oncology, particularly in precision medicine and cancer diagnosis [1][2][3] Group 1: AI in Cancer Diagnosis - The CrossNN AI model developed by Charité University Hospital can analyze the epigenetic features of tumor cells for rapid, non-invasive cancer diagnosis without the need for high-risk surgical biopsies [1][2] - In clinical cases, the CrossNN model achieved a diagnostic accuracy of 99.1% for brain tumors and 97.8% for over 170 cancer types, outperforming most existing AI diagnostic tools [2] - The model's interpretability allows clinicians to trace its diagnostic logic, enhancing the credibility of medical AI [2] Group 2: AI-Assisted Clinical Decision-Making - The Dresden University of Technology team introduced a medical AI agent that integrates large language models and various medical tools to assist oncologists in personalized clinical decision-making [3][4] - In a validation study with 20 simulated cases, the AI agent reached correct clinical conclusions in 91% of cases and accurately referenced cancer guidelines in over 75% of responses [3] - The AI agent aims to reduce "AI hallucinations," thereby improving safety and reliability in clinical settings [3] Group 3: Future Directions and Implementation - The research teams emphasize the importance of integrating AI tools into routine clinical workflows while minimizing disruption to physicians' work [4] - Training for medical professionals is crucial for effective collaboration with AI, ensuring that they retain ultimate clinical decision-making authority [4] - The next steps include developing a "human-machine collaboration mechanism" and prioritizing data security and privacy in system deployment [4]