In the digital age, the need for quick and reliable access to healthcare information is increasingly essential. This project introduces an AI-powered Symptom Checker Application that leverages Natural Language Processing (NLP) and Machine Learning (ML) to interpret user-described symptoms and forecast possible diseases.Through NLP processes such as tokenization, lemmatization, and Named Entity Recognition (NER), the application converts free-form text into structured data. This processed information is then analyzed by ML models like Naïve Bayes, Random Forest, and Support Vector Machine (SVM) to estimate probable medical conditions.Acting as a virtual medical assistant, the system offers users an initial understanding of their health concerns, helping them make informed decisions before consulting a doctor. By integrating AI technologies, the project enhances healthcare accessibility, supports preventive diagnosis, and minimizes misinformation from unreliable sources.
Rising levels of carbon emissions have emerged as a key factor to climate change requiring smart mechanisms of monitoring and mitigation. In this paper, CarbonIQ, a machine learning-based, generative AI-based, and IoT-based data collection integrated carbon footprint prediction a…
In the era of modern technologies, introduced the widespread use of cloud computing and other solutions that revolutionized the storage and management of information. Cloud-based network threat identification and risk management using applying Log Analysis and Machine learning is…
Cardiovascular disease (CVD) remains the leading cause of global mortality, necessitating non-invasive, accurate, and interpretable screening tools. Retinal fundus imaging offers an accessible, low-cost means of assessing systemic vascular condition, since microvascular changes v…
Chronic Kidney Disease (CKD) is a serious, progressive, and widely known medical condition that afflicts millions around the globe and often is not diagnosed until it has reached its later stages. Healthcare systems face obstacles in the timely diagnosis of CKD, due to the gradua…
Modern microblogging and social networking ecosystems serve as massive, continuous streams of public expression, generating expansive volumes of multilingual data that reflect global consumer sentiments and emotional trends. Parsing actionable insights from this cross-lingual tex…
Modern surveillance systems often struggle to detect and respond to threats in real time. This paper introduces a system that uses context-aware threat intelligence to detect weapons, recognize violent actions, analyze time-based patterns, and assess potential threats based on th…