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Payal Parshuram Patil, Snehal G. Pal
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- Research Scholar, Research Scholar, Thakur Institute of Management Studies, Career Development & Research (TIMSCDR), Mumbai, Thakur Institute of Management Studies, Career Development & Research (TIMSCDR), Mumbai, Maharashtra, Maharashtra, India, India
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Abstract
nIn today’s world, taking care of your wellbeing is of most extreme significance. The multiplication of wellbeing issues could be a genuine burden on specialists around the world, making it troublesome to viably treat each persistent. To ease the burden on specialists, there have been noteworthy progressive thoughts that have changed the healthcare industry. With the movement of computer innovation, it gets to be conceivable to create comes about more precisely and quickly. This, in turn, encourages the arrangement of treatment custom-made to person patients. Identifying cancer at an early organize is still a challenge in healthcare. The World Wellbeing Organization emphasizes that the determination and disposal of cancer cells are attainable when identified in their early stages. Subsequently, the basic for early location of cancer cells emerges as a need to relieve the challenges related with cancer. Out of all the distinctive sorts of cancer, breast cancer patients are at the beat. Various ladies are helpless to breast cancer, underscoring the centrality of identifying these cancer cells to kill them from the patient’s body.
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Keywords: Picture handling, IoT, Breast cancer location, healthcare applications
n[if 424 equals=”Regular Issue”][This article belongs to International Journal of Advanced Robotics and Automation Technology(ijarat)]
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References
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- Shahirah Zahir,” Applying the Deep Learning Model on an IoT Board for Breast Cancer Detection based on Histopathological Images”,Available:- “https://iopscience.iop.org/article/10.1088/1742-6596/1755/1/012026/meta”
- s salvi, “Breast cancer detection using Seep Learnig“,available:- “https://iopscience.iop.org/article/10.1088/1742-6596/1831/1/012030/meta”
- M H memon,” Breast cancer detection in the IOT health environment using modified recursive feature selection“,Available:- “https://www.hindawi.com/journals/wcmc/2019/5176705/abs/”
- S Mishra,“Medical internet-of-things based breast cancer diagnosis using hyperparameter-optimized neural networks”,Available:- “https://www.mdpi.com/1999-5903/14/5/153”
- VN Gopal,”Feature selection and classification in breast cancer prediction using IoT and machine learning”,available:-“ https://www.sciencedirect.com/science/article/pii/S0263224121004310”
- R Majji,” Smart IoT in Breast Cancer Detection Using Optimal Deep Learning”, Available:-“ https://link.springer.com/article/10.1007/s10278-023-00834-9”
- U K Lihore ,” Breast cancer detection in the IoT cloud-based healthcare environment using fuzzy cluster segmentation and SVM classifier”, Available:-“ https://link.springer.com/chapter/10.1007/978-981-16-7952-0_16”
- Sandhu JK, Kaur A, Kaushal C. A Review of Breast Cancer Detection Using the Internet of Things and Machine Learning. In2023 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE) 2023 Mar 9 (pp. 145-150). IEEE.
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International Journal of Advanced Robotics and Automation Technology
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| Volume | 01 | |
| [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] | 02 | |
| Received | March 11, 2024 | |
| Accepted | March 19, 2024 | |
| Published | April 25, 2024 |
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