Stillbirth is strongly related to impaired fetal growth. Perinatal loss, commonly defined as stillbirth is the death of a fetus before birth. This condition can be brought on by intrauterine growth restriction and poses significant financial, physical, and psychosocial challenges for families. The latest rate of stillbirth and low birth weight in India is 17.3% and 18.24% respectively which is significantly higher in rural areas than in urban areas. This study introduces an integrated analysis pipeline tailored to elucidate the prevalence of stillbirth in India. Leveraging PubMed data using keywords like low birth weight, stillbirth, fetal mortality, perinatal loss, and preterm birth, we assembled a comprehensive dataset containing PubMed IDs, author information, titles, years, journal details, countries, abstracts, and publication types. Employing natural language processing (NLP), we identified factors linked to stillbirth. The analysis utilized Python programming with biopython and scikit-learn packages, and visualization methods such as bar charts, pie charts, and word clouds were employed to depict the trends and geographical distribution of stillbirth cases over time. Despite India's economic growth and increased public health investment in nutritional support, the burden of stillbirth has remained steady in recent years. There is a crucial need to prioritize the quality of antenatal care services for pregnant women, focusing on raising awareness and sensitization to improve maternal nutrition.