With the advancement in the field of Artificial Intelligence, there have been considerable efforts to develop technologies for pattern recognition related to medical diagnosis. Artificial Neural Networks (ANNs), a significant piece of Artificial Intelligence forms the base for most of the marvels in the former field. However, ANNs face the problem of premature convergence at a local minimum and inability to set hyper-parameters (like the number of neurons, learning rate, etc.) while using Back Propagation Algorithm (BPA). In this paper, we have used the Genetic Algorithm (GA) for the evolution of the ANN, which overcomes the limitations of the BPA. Since GA alone cannot fit for a high-dimensional, complex and multi-modal optimization landscape of the ANN, BPA is used as a local search algorithm to aid the evolution. The contributions of GA and BPA in the resultant approach are adjudged to determine the magnitude of local search necessary for optimization, striking a clear balance between exploration and exploitation in the evolution. The algorithm was applied to deal with the problem of Breast Cancer diagnosis. Results showed that under optimal settings, hybrid algorithm performs better than BPA or GA alone.

BACKGROUND: Candidemia refers to the isolation of pathogenic species of Candida from a blood culture specimen. Candidemia in hospitalized patients especially in ICU patients is emerging as a signicant problem worldwide. Isolation of an organism from a blood culture of a neonate with clinical symptoms of infection constitutes the common denition of sepsis. The change in epidemiology and pattern of antifungal susceptibility of Candida infection has made identication of aetiological agent compulsory along with its antifungal susceptibility. MATERIALS AND METHODS: This retrospective cross - sectional study was carried out in the neonatal intensive care unit of tertiary health care centre, Lata Mangeshkar Hospital, Nagpur during the period of March 2021 to September 2021 with the primary objective to determine the incidence of fungal sepsis in very low birth weight neonates in neonatal intensive care unit (NICU) setup and secondary objective to study the correlation with the risk factors in a tertiary care center in India. RESULTS: In the present study, between march 2021 to September 2021, out of total 47 very low birth neonates, 18 very low birth weight neonates were blood culture positive for candida species . Hence, the incidence of candidemia in Very Low Birth Weight neonates in this study was 36%. DISCUSSION: The increase in resistance to antifungal agents among Candida isolates has resulted in increased mortality and morbidity. Prevention of risk factors in Candidemia patients with early removal of central line, timely fungal culture, Candida speciation and antifungal susceptibility are necessary for appropriate treatment and better outcome. CONCLUSION: Neonatal Candida colonization is the rst step that predisposes to invasive candidiasis. Pregnancies complicated by preterm labor or possible delivery should be considered for screening and treatment of maternal vaginal colonization to decrease the occurrence of neonatal colonization and its sequences