# Artificial Intelligence in Ophthalmology: Advantages and Limits
## 4 Representative Areas of Application of AI in Ophthalmology
### Artificial Intelligence and Cataract
#### 4.1.2 Limitations of Current Clinical Procedures  
There are four categories of such limitations in the case of cataract disease.  
Case Detection Programs  
Nowadays, cataract disease is clinically assessed on slit-lamp inspection, using the System of Lens Opacities Classification (LOCS) III, also used to recommend the type of treatment required.  
This assessment needs clinical expertise, training, and valuable equipment for clinical decision-making, which is an important challenge for poor or developing countries or rural environments. Furthermore, image-based grading scores are not objective and can be notably influenced by inter- and intra-equipment variations. These kinds of limitations are such that screening for cataracts is time-consuming and costly. In this way, there is a significant need to deploy new techniques that can handle such limitations and help in screening cataracts.  
Calculation of Intraocular Lens (IOL) Power  
The usual procedure for cataract treatment is surgery followed by IOL implantation to restore vision. Cataract surgery planning is essentially determined by IOL power calculation, which depends on parameters such as axial length, effective lens position, corneal curvature, and the type of IOL chosen.  
This calculation is performed quickly using biometric machines, but due to the large variation in eye biometrics between individuals, there is currently no unique formula suitable for all patients. Additionally, it cannot be used for eyes with non-usual corneal shapes, such as eyes with previous refractive surgery, keratoplasty, keratoconus, microcornea, or significant astigmatism.  
Through the use of AI, ML, and databases, new IOL formulas have been studied that can be efficiently used for a subgroup of patients. In this respect, in the coming years, we may face major developments.  
Workforce Training and Surgical Evaluation  
For approaching the needs of the aging population, the current number of ophthalmologists should increase by 75-100% in the next 20 years.  
An important aspect of current training for surgeons in ophthalmology is the necessity of extensive patient exposure, which is often not available. This involves a significant investment in training costs and the time required to develop skills. Techniques such as virtual reality (VR) [60] and augmented reality (AR), \"wet\" laboratories, training courses, and didactic videos are the main instruments for teaching the best surgical techniques.  
Postoperative Care and Quality of Life (QoL)  
Appropriate postoperative care is a very important characteristic of any surgery. With the increased use of digital technologies in patient diagnosis, treatment, and management of medicines, the importance of AI will increase in the future. Live telecosultations, chatbots, and tele-simulated assistants will be used for telecosultation and feedback collection, various mobile applications and digital health monitoring will increase in the coming years. For example, it is possible to predict the risk of complications such as posterior capsular opacification in post-cataract surgery by means of artificial neural networks (ANNs) [61].