INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Artificial machines using learning and Neural networks offer faster and more accurate solutions to the problems faced by oncologists. The use of artificial intelligence is likely to grow exponentially. However, the primary responsibility for concerns about the patient population, social inequalities, and wisdom reports regarding the disease and its natural course will rest with the physician. Artificial Intelligence (AI) is likely to bridge the gap between knowledge acquisition and knowledge acquisition. Its meaning is explained. This method has been shown to outperform most classification and regression methods to date and is able to learn data representations best suited to the tasks held and presented, becoming better for the respective process. This article attempts to convince radiologists about the role of AI and their goal to achieve more. The paper discusses a number of oncology topics, with a focus on radiation oncology as this is the arena where AI-based research has been conducted. AI has improved patient survival and result definition by precisely characterizing several aspects of healthcare, including prognostic tests, diagnosis, and screening modalities. AI-based techniques are now being used in radiation oncology for a number of protocols and procedures, including radiation delivery, segmentation, and planning. AI's benefits for the health industry as a whole might soon result in more advanced, individualized medicine
Keywords:
Convolutional neural networks, radiation oncology, artificial intelligence, machine learning, deep learning, and planning
Cite Article:
"“Putting Together Surgical Prioritie: The Fusion of Immunology and Robotics”", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.d442-d453, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404350.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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