AI-based tool for early detection of Alzheimer's disease.

In the context of Alzheimer's disease (AD), timely identification is paramount for effective management, acknowledging its chronic and irreversible nature, where medications can only impede its progression. Our study introduces a holistic solution, leveraging the hippocampus and the VGG16 model with transfer learning for early AD detection. The hippocampus, a pivotal early affected region linked to memory, plays a central role in classifying patients into three categories: cognitively normal (CN), representing individuals without cognitive impairment; mild cognitive impairment (MCI), indicative of a subtle decline in cognitive abilities; and AD, denoting Alzheimer's disease.

Evaluation of macular and peri-papillary blood vessel density following uncomplicated phacoemulsification in diabetics using optical coherence tomography angiography.

Purpose: The aim of this study was to evaluate the macular and peri-papillary blood vessel density following uncomplicated phacoemulsification in diabetics using optical coherence tomography angiography (OCT-A).

Methods: An observational case-control study was conducted on 60 patients eligible for phacoemulsification, divided equally into diabetic and control groups. Both study groups were matching in sex, age, and axial length.