Evolving and novel applications of artificial intelligence in interventional oncology

Table 2 Current and potential patient-focused artificial intelligence applications and validation gaps in interventional oncology

Application	Description	Highest level of clinical evidence currently available	Most significant validation gap	Ref.
Patient selection & response prediction	Analyzes clinical data to predict therapeutic response, enabling patient-specific treatment recommendations while accounting for potential risks	Retrospective studies, simulation platforms, some prospective modeling	Lack of prospective trials and integration into real-time clinical decision-making	[41,54,55,60-63,67,111,115]
Patient triage	Prioritizes patients for urgent interventional oncology procedures by evaluating imaging and clinical indicators of disease severity	Retrospective validation in diagnostic settings	Limited IO-specific validation and real-time deployment in procedural prioritization	[128]
Personalized post-procedural follow-up and long-term management	Integrates clinical, procedural, and imaging data to customize follow-up schedules and management plans, improving patient outcomes over time	Retrospective studies, mobile health feasibility trials	Lack of prospective trials with integration with EMRs and imaging systems	[23,111-113,115,116,129,130]
Improved patient experience	Delivers personalized education, procedural tours, and recovery support to foster a more comfortable and informed perioperative experience	Feasibility studies and pilot implementations, RCT	Limited usability testing and lack of standardized patient outcome metrics	[129,133,134]
Comprehension enhancement	Provides clear, individualized instructions, interactive virtual tours, and tailored recovery feedback to improve patient understanding and adherence	Systematic reviews and NLP-based readability studies	Lack of prospective validation and integration into clinical education workflows	[129,131-134]

IO: Interventional oncology; EMR: Electronic medical record; RCT: Randomized controlled trial; NLP: Natural language processing.