http://repository.iiitd.edu.in/xmlui/handle/123456789/1008 Thu, 03 Sep 2026 04:09:00 GMT 2026-09-03T04:09:00Z http://repository.iiitd.edu.in/xmlui/handle/123456789/2081 Title: AyurIntel: the intelligent ayurvedic assistant for cancer research and epigenetic insights Authors: Rawat, Arun Singh; Dhanjal, Jaspreet Kaur (Advisor) Abstract: AyurIntel is a knowledge-based AI system created to connect classical Ayurvedic texts with modern oncology. It does this by using knowledge extraction, biomedical NLP, and generative AI (LLMs with RAG). The primary goals of this project are to: • Organize and structure scattered Ayurvedic knowledge • Extract and integrate insights from biomedical literature • Enable accessible, conversational interaction with the unified dataset via a chatbot and visual knowledge graph We used sources like the Charaka Samhita, PubMed, ClinicalTrials, and AYUSH Monographs. We applied techniques such as NER, Sanskrit NLP, OCR, and a knowledge graph (Ayurtator). The final system features a chatbot interface powered by RAG+GPT and a web interface with graph-based visualizations. Tue, 01 Jul 2025 00:00:00 GMT http://repository.iiitd.edu.in/xmlui/handle/123456789/2081 2025-07-01T00:00:00Z http://repository.iiitd.edu.in/xmlui/handle/123456789/2080 Title: Application of machine learning for computational gastronomy Authors: Singh, Jaskaran; Bagler, Ganesh (Advisor) Abstract: Using the FlavorDB database, this study creates a machine learning model for categorizing ingredients based on their molecular composition. The study aims to classify 936 food components into 35 flavor categories by evaluating their chemical structures. The methodology used several critical techniques, including data preparation with one-hot encoding of molecular makeup, class imbalance resolution with SMOTE (Synthetic Minority Over-sampling Technique), and data standardization with StandardScaler. Several machine learning methods were tested, including Random Forest, Extra Trees, Neural Networks, LightGBM, and others. The Random Forest Classifier outperformed expectations, with an F1-score of 81.02% and an accuracy of 79.52%. A stacking ensemble strategy was also investigated, which combined numerous base models with a Random Forest meta-model and achieved an average accuracy of 71.52%. Advanced analytical techniques that complement the primary classification include, Principal Component Analysis (PCA) to reduce dimensionality, SHAP (SHapley Additive Explanations) analysis is used to interpret feature importance and, the ROC-AUC curve analysis revealed a nearly flawless integrated AUC score of 0.99. The study emphasizes the potential of machine learning in computational gastronomy by providing a novel way to ingredient classification using molecular data analysis. Tue, 26 Nov 2024 00:00:00 GMT http://repository.iiitd.edu.in/xmlui/handle/123456789/2080 2024-11-26T00:00:00Z http://repository.iiitd.edu.in/xmlui/handle/123456789/2079 Title: Understanding postpartum depression: the parental awareness and self-perception Authors: Singh, Navnoor; Kacker, Twisha; Mishra, Paro (Advisor) Abstract: Postpartum Depression (PPD) is a significant mental health condition that affects parents, especially mothers, with estimates suggesting that as many as 1 in 7 women may experience this condition globally. Characterized by symptoms such as severe mood swings, anxiety, irritability, and difficulties in bonding with the infant, PPD can substantially impair a mother's functioning and quality of life, as well as her relationship with her child and family. Despite its prevalence, PPD frequently remains undiagnosed, with nearly half of affected mothers not receiving the necessary treatment, compromising the urgent need for awareness and support. The causes of PPD are multifaceted, involving a combination of hormonal changes, psychological factors, and social conditions. Women with a history of depression, lack of social support, or significant life stressors are particularly at risk. Research has identified various risk factors, including obstetric complications and previous depressive episodes, which contribute to the onset of PPD. Early recognition and intervention are crucial, as effective treatments such as psychotherapy, medication, and support networks can mitigate symptoms and facilitate recovery. Notably, the impact of PPD extends beyond the mother, affecting the emotional and cognitive development of infants and straining family dynamics. Children of mothers who suffer from untreated PPD may face long-term developmental challenges, while the emotional toll can also affect partners and family members. Addressing PPD through preventive measures and comprehensive treatment strategies is essential for enhancing maternal mental health and fostering healthy family environments. Controversies surrounding PPD include the stigma attached to maternal mental health issues and the variability in treatment accessibility, particularly in underserved populations. This has spurred ongoing discussions about improving healthcare policies and support systems to serve better women experiencing postpartum mental health challenges. Wed, 27 Nov 2024 00:00:00 GMT http://repository.iiitd.edu.in/xmlui/handle/123456789/2079 2024-11-27T00:00:00Z http://repository.iiitd.edu.in/xmlui/handle/123456789/2077 Title: A sociological study of intending parents’ attitudes towards donor gametes in IVF in India from the perspective of fertility specialists Authors: Khurana, Sejal; Mishra, Paro (Advisor) Abstract: This research delves into the sociological dimensions of couples’ attitudes toward donor gametes, emphasizing the critical role of doctors as facilitators of Assisted Reproductive Technologies (ARTs). By examining gamete donation—a process central to ARTs—through a thematic analysis of 23 academic studies, the study categorizes findings into four primary actor groups: donors, recipients, traders, and doctors. The research identifies major themes such as confidentiality, commodification, sociocultural influences, and emotional impacts, highlighting the ethical and logistical challenges inherent in gamete donation. This analysis highlights the interplay among stakeholders, offering insights into how ARTs practices are shaped by diverse cultural and social dynamics. The larger project aims to explore these themes further by conducting primary research through interviews with IVF and infertility specialists in Delhi NCR, focusing on their perspectives on patients’ responses to donor gametes. So far, the study has reviewed relevant literature and categorized key themes, providing a foundation for the upcoming qualitative re- search phase, which will deepen the understanding of ARTs practices from a clinical and cultural standpoint. Sun, 01 Dec 2024 00:00:00 GMT http://repository.iiitd.edu.in/xmlui/handle/123456789/2077 2024-12-01T00:00:00Z