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@article{163163,
        author = {K.Balaji and K. Aswin and A.Hemanth Chowdari and V. Bala Murugan and V. Ethirajulu},
        title = {Predicting Low Birth Weight Cases Using Deep Learning Approach For Early Detection},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {11},
        pages = {805-813},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=163163},
        abstract = {Low Birth Weight is the major problem for the new born. Low birth weight is a term used to describe babies who are born weighing less than 5 pounds, 8 ounces (2,500 grams). Low-birth weight babies are more likely than babies with normal weight to have health problems as a newborn. Almost 40 percent of the new born suffer from underweight. Predicting birth weight before the birth of the baby is the best way to help the baby get special care as early as possible. It helps us to arrange for doctors and special facilities before the baby is born. There are several factors that affect the birth weight. Through past studies, it has been observed that the factors which affect the child birth range from biological characteristics like the baby's sex, race, age of mother and father, weight gained by the mother during pregnancy to behavioral characteristics like smoking and drinking habits of the mother, the education and living conditions of the parents. Our system is an live detection model and periodic analysis of mother and detecting physical levels in her by providing them with proper remedies for managing LBW by providing survey form periodically.},
        keywords = {LBW, Smoking, Drinking habit, Biological, Pregnancy},
        month = {},
        }