http://hdl.handle.net/123456789/97 Wed, 15 Jul 2026 16:07:15 GMT 2026-07-15T16:07:15Z http://hdl.handle.net/123456789/21494 THERAPEASE: COMPREHENSIVE CARE FOR PSYCHOTHERAPY Usmani, Mahmed Reg # 79001; Asif, Hunain Reg # 79737; Akram, Hamad Reg # 79906 The delivery of mental health services has experienced a tremendous demand for advanced digital therapy platforms which provide efficiency alongside security together with ease of use. TheraEase serves as a web-based platform which implements a standardized system that uses automated processes for therapist-client communication alongside administrative control features and artificial intelligence support. The system enables administrator-approved credential verification to activate therapists securely after their approval. The system allows therapists to schedule sessions, monitor income flow, request withdrawal payments subject to approval and can browse therapists, schedule view payment documentation and clients appointments and request reimbursement that requires administrative approval. The main innovation within TherapEase involves its automated capabilities powered by AI technology. The screening process for clients includes an analysis done with the combination of Sementic search and LLM reasoning which recommends a specific psychotherapy scales based on client responses. AI proceeds client screening by producing specialized client’s profile. Each therapy session generates an automated report that first transcribes audio files while performing speaker diarization, then sends the information to Gemini for analysis before creating a formatted document which is permanently removed from storage for privacy purposes. The platform promotes use accessibility through form filling enabled by Web Speech API which allows clients to speech-to-text functions. Among their core responsibilities Admins control all operational aspects from therapist/client administration to refund processes and payout procedures as well as generating analytics that encompass revenue data and appointment scheduling and user statistical information. Supervised by Dr. Raheel Siddiqui Wed, 01 Jan 2025 00:00:00 GMT http://hdl.handle.net/123456789/21494 2025-01-01T00:00:00Z http://hdl.handle.net/123456789/21492 MENTAL AND EMOTIONAL HEALTH SUPPORT SYSTEM USING CBT-BASED LLM Farrukh, Ahmed Reg # 78993; Yousuf, Shavana Reg # 79241 Despite stigma, high costs, and resource scarcity, mental health challenges are increasingly afflicting people in all generations, but support on time, in personal and affordable manners, is still not easily reached. For this reason, Artificial Intelligence is taking on a nurturing role as a means of augmenting emotional support and scale Generative AI-Based Mental delivery of therapeutic interventions. In this project, a and Emotional Health Support System is presented, which is built upon a modular agent-based architecture to simulate a CBT inspired support. The system is built using the Gemini API and LangChain, integrating nine specialized tools such as a Retrieval Tool (Pinecone), Mood Analysis, Thought Reframing, Crisis Detection, Reflective Listening and a Web Search component (Tavily). The tool set consists of each tool as central executor that dynamically agent coordinated through a an autonomous determine user input and select the appropriate tool for instance and intent. The prompt engineering is based on modular template design with structured instructions, persona and few shot learning to guarantee tone, safety and coherence. Retrieval in relation to scientifically validated settings Augmented Generation (RAG) puts responses factual accuracy. It has a private and seamless mental health literature to increase interaction through a Streamlit interface. Crisis detection and topic filtering provide ethical safeguards to protect the user. Users and psychologists had posmve feedback on the system as a potential reliable and emotionally intelligent digital mental health companion. Supervised by Muhammad Shahid Khan Wed, 01 Jan 2025 00:00:00 GMT http://hdl.handle.net/123456789/21492 2025-01-01T00:00:00Z http://hdl.handle.net/123456789/21490 SEHAT - A MULTIPURPOSE HUB FOR YOUR HEALTH AND WELLNESS NEEDS Siddiqui, Muhammad Saad Reg # 79015; Wahid, Abdul Rehman Abdul Reg # 79249; Yamin, Hashir Bin Reg # 79903 In today’s fast-paced world, people often neglect key aspects of their health due to fragmented health monitoring tools and lack of time for routine checkups. There is a growing need for a unified, intelligent solution that empowers users to manage their overall well-being in provide citizens easier and more precise now ways to one place. Mobile health (mHealth) applications observe different aspects of their personal health. The current mobile health apps specific domain while overlooking others which leads to divided health concentrate on one data among users. This project delivers SEHAT - A Multipurpose Hub for Health and Wellness Needs as a single mobile application platform that contains three essential health monitoring features: Sleep Tracker, Nutrition Tracker, and Disease Prediction. The system implements a ffontend built with Flutter and a backend with Django to achieve responsive performance along with a scalable structure. The application uses artificial intelligence to improve two main features: it recognizes meals by processing images and predicts diseases such as diabetes along with hypertension and diabetic retinopathy. These A1 models receive training from and perform evaluations on information obtained from public databases. SEHAT unites diverse health services through its unified platform to deliver an improved system for comprehensive whole-person health care management. Supervised by Fasiha Ikram Wed, 01 Jan 2025 00:00:00 GMT http://hdl.handle.net/123456789/21490 2025-01-01T00:00:00Z http://hdl.handle.net/123456789/21493 SMART RESUME PARSER: AUTOMATED RESUME SCREENING AND ANALYSIS SYSTEM Ahmed, Maaz Reg # 79250; Furqan, Muhammad Reg # 79019; Paracha, Abdul Mueed Reg # 79736 Recruiters, however, have to spend many hours manually screening resumes of hundreds of candidates for each hiring process because the competitive job market demands it. There is no good resume screening system that goes through job requirements and therefore a waste of opportunities between job seekers and employers. The project that I would like to present is Smart Resume Parser: Automated Resume Screening and Analysis System, which is a smart solution for optimizing the hiring process. The system automatically extracts key information from resume (skills, experience and education) and use such information to evaluate advanced algorithms against job descriptions. Once the system is decently objective and efficient, it gives the recruiters ranked candidate profiles to evaluate. The system has three functions including keyword matching, skill gap analysis, and user enabled filtering tools, and it generates the most appropriate candidate pool. Speeding up the recruiting process and getting candidate assessment right, so the hiring happens fairly and with the help of data, is the result of the automation in Smart Resume Parser. The project purpose is to speed up and smart talent acquisition approach and offer higher efficiency to organizations of any size. Supervised by Reema Qaiser Khan Wed, 01 Jan 2025 00:00:00 GMT http://hdl.handle.net/123456789/21493 2025-01-01T00:00:00Z