A Comprehensive CNN Model for Age-Related Macular Degeneration Classification Using OCT: Integrating Inception Modules, SE Blocks, and ConvMixer.

: Age-related macular degeneration (AMD) is a significant cause of vision loss in older adults, often progressing without early noticeable symptoms. Deep learning (DL) models, particularly convolutional neural networks (CNNs), demonstrate potential in accurately diagnosing and classifying AMD using medical imaging technologies like optical coherence to-mography (OCT) scans. This study introduces a novel CNN-based DL method for AMD diagnosis, aiming to enhance computational efficiency and classification accuracy.

Increased ferritin with contraceptives containing ethinyl estradiol drospirenone in polycystic ovary syndrome: a paradox of iron storage and iron deficiency.

Objectives: The relationship between elevated ferritin levels and metabolic abnormalities in PCOS patients, and whether ferritin is a cause or a consequence, is still debated. This study aimed to evaluate the impacts of the fourth generation combined oral contraceptive containing ethinyl estradiol/drospirenone (EE 30 mcg/DRSP 3 mg), known for its favorable metabolic profile and lower side effect risk, on iron metabolism in PCOS patients, while also exploring the potential relationship between metabolic parameters and iron status.

Methods: The retrospective analysis was conducted on 81 women aged 18-45, diagnosed with PCOS according to the Rotterdam criteria and treated with EE/DRSP for six months.

Enhanced Panoramic Radiograph-Based Tooth Segmentation and Identification Using an Attention Gate-Based Encoder-Decoder Network.

Background: Dental disorders are one of the most important health problems, affecting billions of people all over the world. Early diagnosis is important for effective treatment planning. Precise dental disease segmentation requires reliable tooth numbering, which may be prone to errors if performed manually.

Colloidal quantum dots as solution-based nanomaterials for infrared technologies.

This review focuses on recent progress of wet-chemistry-based synthesis methods for infrared (IR) colloidal quantum dots (CQD), semiconductor nanocrystals with a narrow energy bandgap that absorbs and/or emits IR photos covering from 0.7 to 25 micrometers. The sections of the review are colloidal synthesis, precursor reactivity, cation exchange, doping and de-doping, surface passivation and ligand exchange, intraband transitions, quenching and purification, and future directions.