Page 128 - EJMO-9-1

Eurasian Journal of Medicine and
Oncology
Oncology care with AI chatbots and assistants

Table 1. Identified surveys related to artificial innovations in oncology
Author/s Invention/ Technology Impact Merits Demerits Future
Technology used enhancement
Esteva et al. 6 AI for skin Deep learning, Early detection of High accuracy, Requires Better generalization
cancer detection CNN skin cancer reduced large datasets, across populations
diagnostic time potential bias
Gulshan et al. 7 Eye disease Deep learning, Detection High sensitivity Needs large, Integration with
detection CNN of diabetic and specificity high-quality broader health
retinopathy images systems
Liao et al. 8 AI in breast CNN Enhanced breast Improved Limited dataset Multimodal data
cancer diagnosis cancer detection accuracy in for training AI integration for better
radiographic precision
analysis
Chen et al. 9 AI in Machine Optimized Improved Requires large Real-time adaptive
radiotherapy learning radiation therapy precision, faster clinical data sets radiotherapy with AI
planning plans planning
Wang and Li 10 AI for ovarian Deep learning, Early-stage ovarian Reduced late-stage Data AI for early detection
cancer detection CNN cancer detection diagnosis rates availability in in rural/underserved
underrepresented areas
groups
Liu et al. 11 AI for colorectal Deep learning Early detection Faster diagnosis, Requires Cross-platform
cancer detection through image reduced human validation integration for global
analysis error on diverse use
populations
Rajpurkar et al. 12 Chest X-ray Deep learning, Efficient Reduced Need for Further AI models
diagnosis CNN chest X-ray diagnostic high-quality for varied diagnostic
interpretation workload for annotated data tasks
doctors
Bejnordi et al. 13 AI for pathology Deep learning Improved tissue Enhanced Data quality Automation in
image analysis recognition in diagnostic issues, real-time surgical
pathology capabilities in generalization decision support
pathology problems
Tran et al. 14 AI in prostate CNN Accurate detection Reduces time to High dependence Integration with
cancer detection of prostate cancer diagnosis on dataset size genomics for
personalized
treatment plans
Zhang et al. 15 AI for glioma Deep learning Improved glioma Faster treatment Challenges with More robust
segmentation segmentation planning, more tumor variability algorithms to handle
accuracy accurate diverse tumor
characteristics
Cirillo and Pippa 16 AI for tumor Machine Classifying tumor Faster and Requires AI integration with
classification learning types for treatment more accurate significant precision medicine
classification computational
power
Lee et al. 17 AI in Machine Predicting Personalized Limited to Incorporation of
chemotherapy learning chemotherapy treatment certain types of patient-specific
response efficacy plans, improved cancer genetic data
outcomes
Mazurowski and Buda 18 AI for breast Support vector Predicting Accurate Limited to Real-time prognosis
cancer prognosis machine patient outcomes prognosis trained machine based on continuous
post-surgery prediction models data input
Wang and Li 19 AI in lung cancer Deep learning Early-stage Higher diagnostic Risk of Use in real-time
diagnosis detection of lung precision overfitting with clinical
cancer limited data decision-making
(Cont’d...)

Volume 9 Issue 1 (2025) 120 doi: 10.36922/ejmo.6251