Early diagnosis and clinical decision-making depend on accurate brain tumor classification using magnetic resonance imaging (MRI). However, traditional deep learning methods usually rely on centralized medical data, which raises privacy concerns and limits the use of distributed clinical data. This research proposes a privacy-preserving federated learning framework for MRI image-based binary brain tumor classification using a decentralized ResNet-18 architecture that enables collaborative training without sharing raw patient data. To reflect realistic clinical conditions, the framework integrates heterogeneous multi-source datasets in different image formats (PNG and JPG) and evaluates performance under both IID and non-IID settings

Anastrozole (ANZ) is considered constitute of the fourth –generation of Non–steroidal aromatase blockage, ANZ has use for hormone receptor positive breast cancer in postmenopausal women. The serious side effects of ANZ including, vaginal dryness, hot flashes, irritability, breast tenderness and un–stability in circulation.

Nanostructured lipid carriers (NLCs) have recently emerged as a multifunctional platform for drug delivery in cancer therapy.

Five formula were composed of (200 mg of glyceryl monostearate, 40 mg of oleic acid , 1% (w/w) Tween 80, 1% (w/w) Poloxamer 407, 1% (w/w) soy lecithin and Vitamin E Polyethylene Glycol Succinate.

The mean particle size, polydispersity index, zeta potential, entrapme