Hello there! I'm Nandini Sharma, a passionate and dedicated final year MCA (Christ University) student with a keen interest in software & web development and problem-solving. My journey in the realm of technology has equipped me with a strong foundation in various programming languages, web development, and database management.Throughout my academic pursuits, I've actively engaged in projects that showcase my versatility and ability to adapt to new challenges. My goal is to leverage my skills and knowledge to contribute innovative solutions in the ever-evolving field of computer science. Beyond coding, I am an avid learner, always exploring new technologies and methodologies to stay ahead in the dynamic world of software development.
I'm excited about the possibilities that lie ahead and look forward to making a meaningful impact in the world of technology. Let's connect and explore the future of software together!
The project at hand revolves around addressing the critical challenge of mental health and well-being among the aging population, particularly concerning the complex mental disorder, schizophrenia. As individuals age, they become increasingly susceptible to mental health disorders, which if left unaddressed, can lead to a diminished quality of life and strain healthcare systems. Schizophrenia, characterized by symptoms such as hallucinations, delusions, altered attention, and behavioral changes, presents a unique journey that demands both understanding and empathy. The primary aim of the project is to combat the prevailing social stigma surrounding mental health and schizophrenia. This is achieved through a multi-faceted approach that emphasizes knowledge dissemination, open dialogues, and acceptance. By fostering awareness and empathy, the project seeks to create a supportive environment for those affected by schizophrenia, enabling them to lead more fulfilling lives.
RespiScan can be experienced and used in production as a user-friendly tool for individuals who want to assess their risk of developing lung cancer from the comfort of their own homes. Users can input their basic information and symptoms into the RespiScan model, and receive a prediction of their likelihood of having lung cancer. The model could be integrated into a web-based platform or mobile application, which could be easily accessed by users. The platform could also provide educational resources on lung cancer prevention and early detection, which could help users reduce their risk of developing the disease. Overall, RespiScan has the potential to be a valuable tool for individuals who are concerned about their risk of developing lung cancer, as it can provide a quick and convenient way to assess their risk and take appropriate action to prevent or detect the disease.
RespiScan can be experienced and used in production as a user-friendly tool for individuals who want to assess their risk of developing lung cancer from the comfort of their own homes. Users can input their basic information and symptoms into the RespiScan model, and receive a prediction of their likelihood of having lung cancer. The model could be integrated into a web-based platform or mobile application, which could be easily accessed by users. The platform could also provide educational resources on lung cancer prevention and early detection, which could help users reduce their risk of developing the disease. Overall, RespiScan has the potential to be a valuable tool for individuals who are concerned about their risk of developing lung cancer, as it can provide a quick and convenient way to assess their risk and take appropriate action to prevent or detect the disease.
