Extent of Use of Artificial Intelligence and Machine Learning Protocols in Cancer Diagnosis: A Scoping Review
Author(s)
Dang A1, Dang D2, Vallish BN2, Bhardwaj A3
1MarksMan Healthcare Communications, Hyderabad, AP, India, 2MarksMan Healthcare Communications, Hyderabad, India, 3International Institute of Information Technology, Bhubaneswar, India
Presentation Documents
OBJECTIVES: To explore the extent of actual use of artificial intelligence (AI)/ machine leraning (ML) protocols for diagnosing cancer in prospective settings, given that numerous AI/ ML protocols have shown promising results in cancer diagnosis in validation tests involving retrospective patient databases
METHODS: We searched PubMed for studies that used AI/ML protocols for cancer diagnosis in prospective (clinical trial/ real-world) setting, from inception till 17th May 2021. We looked for studies in which the AI/ML diagnosis actually aided clinical decision making. Data pertaining to the cancer, patients, and the AI/ML protocol were extracted. Comparison of AI/ML protocol diagnosis with human diagnosis was recorded. Through a post-hoc analysis, data from studies describing validation of various AI/ML protocols was extracted.
RESULTS: Only 18/960 initial hits (1.88%) utilised AI/ML protocols for diagnostic decision-making. Most protocols used ANN (artificial neural network) and DL (deep learning). AI/ML protocols were utilised for cancer screening, pre-operative diagnosis, pre-operative staging, and intra-operative diagnosis of surgical specimen. The reference standard for 17/18 studies was histology. AI/ML protocols were used to diagnose cancers of the colorectum, skin, uterine cervix, oral cavity, ovaries, prostate, lungs, and brain. AI/ML protocols were found to improve human diagnosis, and had either similar or better performance than the human diagnosis, especially that made by the less experienced clinician. Validation of AI/ML protocols was described by 223 studies. There was a huge variation in the number of items used for validation.
CONCLUSIONS: A meaningful translation from validation of AI/ML protocols to their actual usage in cancer diagnosis is lacking. Development of regulatory framework specific for AI/ML usage in healthcare is essential.
Conference/Value in Health Info
Value in Health, Volume 25, Issue 12S (December 2022)
Code
MT44
Topic
Medical Technologies
Topic Subcategory
Diagnostics & Imaging
Disease
No Additional Disease & Conditions/Specialized Treatment Areas