A Patient-Doctor-NLP-System to contest inequality for less privileged

Transfer Learning (TL) allowed development, generation and availability of various Large Language Models (LLMs) in Natural language processing (NLP) which emerged and became prevalent in this era. In real environments, training of gigantic LLM is not always feasible and there has been less energies put towards implementation of LLM based solutions that focus the least privileged such as visually impaired or who speak native languages such as Hindi while needing medical support in rural areas. To overcome this challenge, our work demonstrates an initiative which utilize our prescribed PDFTEMRA (Performant Distilled Frequency Transformer Ensemble Model with Random Activations) network. This network incorporates multiple advanced additional modifications to transformer-based structure and utilizes underlying concepts, such as, ensemble, distillation, frequency modulation, random activations, and supplementary forward-thinking scientific renovations.