Smart City Gnosys

Smart city article details

Title Artificial Intelligence Prediction Of The Risk Of Ovarian Cancer At An Early Stage In Smart Cities
ID_Doc 10526
Authors Lavanya J.M.S.; Subbulakshmi P.
Year 2024
Published Healthcare-Driven Intelligent Computing Paradigms to Secure Futuristic Smart Cities
DOI http://dx.doi.org/10.1201/9781032631738-15
Abstract A woman is most likely to develop ovarian cancer, and it is extremely difficult to diagnose the disease in the early stages. Machine learning (ML) is being used for predicting the occurrences of ovarian cancer in women from a very early stage in order to prevent it from progressing to a more difficult stage. Several features of this research are discussed which can be used to predict cancer based on clinical data. This chapter focuses primarily on the use of ML methods for the purpose of predicting cancer at a young age, such as support vector machines (SVMs), decision trees (DTs), and logistic regression (LR). A study was conducted in this paper to determine the performance of various models such as SVMs, DT, and LR for the prediction of early cancer development. In this chapter, an improved method of giving accurate results using a random forest classifier and a random forest feature selection method is presented that uses an integrated approach to provide accurate results by combining feature selection and classifier methods. In comparison to the other models, the proposed model has a higher level of accuracy, 91%, as opposed to 81%, 84%, and 83%, respectively. We draw parallels between our artificial intelligence (AI)-driven ovarian cancer risk prediction model and the overarching vision of smart cities, where data-driven insights and technological advancements converge to shape responsive and efficient urban environments. Integrating our predictive model into smart city frameworks could pave the way for proactive healthcare management, exemplifying the symbiotic relationship between AI-driven healthcare solutions and the realization of intelligent and interconnected urban ecosystems. © 2025 selection and editorial matter, Diptendu Sinha Roy, Mir Wajahat Hussain, K. Hemant Kumar Reddy, Deepak Gupta; individual chapters, the contributors.
Author Keywords


Similar Articles

Id Similarity Authors Title Published
51104 View0.872Prusty S.; Dash S.K.; Prusty S.G.P.; Dalai S.S.; Tripathy N.; Nayak S.K.Smart Iot_Cloud-Based Ml Technique To Classify Breast Cancer2023 2nd International Conference on Ambient Intelligence in Health Care, ICAIHC 2023 (2023)
8311 View0.87Ray S.S.; Tripathy N.; Tripathy S.S.; Gheisari M.An In-Depth Analysis Of Machine Learning And Artificial Intelligence Advancements In Healthcare For Smart CitiesHealthcare-Driven Intelligent Computing Paradigms to Secure Futuristic Smart Cities (2024)
14508 View0.861Malathy N.; Sophia J.G.; Harini R.S.; Ramya M.Cluster Weighting—A New Clustering Technique For Outlier Removal And Noise Overlap In Healthcare Diagnosis For Smart CityHealthcare-Driven Intelligent Computing Paradigms to Secure Futuristic Smart Cities (2024)
35881 View0.859Pasupuleti V.; Thuraka B.; Kodete C.S.Machine Learning And Big Data Analytics In Smart Cities And Healthcare: Applications, Challenges, And Future Directions2024 International Conference on Computer and Applications, ICCA 2024 (2024)
51097 View0.857Subashini P.; Dhivyaprabha T.T.; Krishnaveni M.; Susan M.B.J.Smart Intelligent System For Cervix Cancer Image Classification Using Google Cloud PlatformEnabling Technologies for Effective Planning and Management in Sustainable Smart Cities (2023)
51010 View0.853Bhute H.; Wani R.; Patil N.; Naik V.Smart Healthcare In Smart Cities: Leveraging Machine Learning For Disease Detection2024 4th International Conference on Intelligent Technologies, CONIT 2024 (2024)
836 View0.851Gupta T.; Panda S.P.A Comparison Of Machine Learning Algorithms In Predicting Pulmonary Diseases2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing, COM-IT-CON 2022 (2022)