Novel automated non-invasive detection of ocular surface squamous neoplasia using artificial intelligence

Table 1 Entities included in the term ‘ocular surface squamous neoplasia’

Term	Description	Structures included	First introduced
Epithelioma[1]	A generalized term encompassing neoplastic proliferation of the ocular surface epithelium, subsequently identified as squamous cell carcinoma of the conjunctiva and cornea	Conjunctiva and cornea	1860
Conjunctival Intraepithelial Neoplasia[2]	Abnormal neoplastic tissue involving the epithelium of the conjunctiva alone or the cornea as well	Conjunctiva and cornea	1978
Corneal Intraepithelial Neoplasia[2,3]	Disordered epithelial maturation (dysplasia) associated with abnormal growth of the corneal epithelium	Cornea	1984
Conjunctival and corneal invasive neoplasia[4]	Invasion of abnormal neoplastic tissue involving the epithelium of the conjunctiva or cornea	Conjunctiva or cornea	1986

Table 2 Various advantages of integrated artificial intelligence in automated screening

Advantages of automated screening by AI for OSSN
It enables the screening process to be more efficient and objective, reducing the reliance on subjective human interpretation
AI algorithms can analyze large volumes of images rapidly and consistently, aiding in the early identification of suspicious lesions that may otherwise be overlooked
Automated screening can enhance access to care, particularly in areas where specialized ophthalmic expertise may be limited, through telemedicine and remote monitoring
By providing a preliminary assessment of OSSN lesions, AI technology can support primary care providers and community healthcare workers in triaging patients and referring those in need of further evaluation to specialized centers
AI-driven automated screening holds promise in improving the early detection and management of OSSN, ultimately leading to better patient outcomes

AI: Artificial intelligence; OSSN: Ocular surface squamous neoplasia.

Table 3 Various advantages of artificial intelligence-based evaluation of severity in ocular surface squamous neoplasia

Advantages of AI-based evaluation of severity in OSSN
It provides an objective and standardized assessment, reducing interobserver variability that may be present in traditional evaluation methods AI algorithms can analyze large amounts of data rapidly and consistently, ensuring accurate and reproducible severity evaluation
Additionally, AI can incorporate multi-modal data, including imaging findings from techniques such as OCT, confocal microscopy, or histopathological characteristics
This integration of diverse data sources enhances the accuracy and reliability of severity evaluation, enabling clinicians to make informed decisions regarding treatment planning and prognostication
Overall, AI-driven evaluation of severity in OSSN holds promise in improving patient outcomes by facilitating appropriate and tailored management strategies based on the individual characteristics of each case

AI: Artificial intelligence; OCT: Optical coherence tomography; OSSN: Ocular surface squamous neoplasia.

Table 4 Various advantages of integrated artificial intelligence in ocular surface squamous neoplasia

Advantages of integrated AI in OSSN
AI algorithms would analyze large volumes of data with speed and accuracy, surpassing human capabilities in terms of processing efficiency
This capability would allow for rapid and efficient screening, diagnosis, and evaluation of OSSN lesions, saving valuable time and resources for healthcare professionals
AI models would progressively learn from vast datasets, enabling them to identify increasingly complex patterns and subtle features that may be challenging for human observers to detect
This ability would offer enhanced diagnostic accuracy and aid in early detection, potentially improving patient outcomes and prognosis
AI would provide a standardized and objective assessment, reducing interobserver variability and ensuring consistent and reliable evaluations of severity, classification, and staging
By leveraging AI technology, clinicians would benefit from enhanced decision support, optimized treatment planning, and personalized management strategies for OSSN patients

AI: Artificial intelligence; OSSN: Ocular surface squamous neoplasia.