Artificial Intelligence- Oncology and Central Nervous System Tumour Detection

In recent times, in this world of science and technology and recent advancements like machine learning and artificial intelligence, clinicians and medical science are supported with better treatment assistance, increased efficiency and improved methodology in the detection of even the rarest tumour...

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Main Authors: Zotey Vaishnavi, Ambad Ranjit, Lamture Yashwant Ramrao, Jha Rakesh Kumar
Format: Article
Language:English
Published: EDP Sciences 2024-01-01
Series:E3S Web of Conferences
Subjects:
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/21/e3sconf_icecs2024_04002.pdf
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author Zotey Vaishnavi
Ambad Ranjit
Lamture Yashwant Ramrao
Jha Rakesh Kumar
author_facet Zotey Vaishnavi
Ambad Ranjit
Lamture Yashwant Ramrao
Jha Rakesh Kumar
author_sort Zotey Vaishnavi
collection DOAJ
description In recent times, in this world of science and technology and recent advancements like machine learning and artificial intelligence, clinicians and medical science are supported with better treatment assistance, increased efficiency and improved methodology in the detection of even the rarest tumour in the human body. In the field of oncology, the help of AI has proved promising results. Diagnosing by imaging and detecting gliomas, its grading can be done easily and accurately. This article focuses on recent advances and technologies in the field of AI and CNS Brain tumour detection. Rare and difficult tumours hard to detect and identify can now be seen and classified with the help of these newer technologies. Pre Intra and post-operative strategies can be planned accurately and most precisely with the help of AI. It is a vast concept that helps enhance various human cognitive abilities in wide ranges.Deep Learning, one of the types of ML, has proved effective in automating many time-consuming steps, including lesion detection and segmentation. AI has several features such as detection and classification, tumour molecular properties, cancer-linked genetics, discoveries of various drugs, prediction of treatment, its outcomes as well as survival, and continued trends in personalized medicine in CNS tumours such as GBM with poor prognosis. Artificial Intelligence is a vast concept that helps enhance various human cognitive abilities in wide ranges. This review focuses on the recent advances in AI and its use in oncology, specifically in CNS, detection, and assessment planning of the underlying cause. Promises and challenges of the same are discussed below.
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spelling doaj.art-2e0e346aeeb84a00ba9023b7d9505cc52024-02-23T10:21:00ZengEDP SciencesE3S Web of Conferences2267-12422024-01-014910400210.1051/e3sconf/202449104002e3sconf_icecs2024_04002Artificial Intelligence- Oncology and Central Nervous System Tumour DetectionZotey Vaishnavi0Ambad Ranjit1Lamture Yashwant Ramrao2Jha Rakesh Kumar3Undergraduate student, Jawaharlal Nehru Medical College , Wardha.Datta Meghe University of Medical SciencesProfessor Dept. of Biochemistry Dr. Rajendra Gode Medical CollegeProfessor, Department of General Surgery, Jawaharlal Nehru Medical College, DattaMeghe University of Medical Sciences, Wardha, Maharashtra, India.Tutor , Dept. of Biochemistry Dr. Rajendra Gode Medical CollegeIn recent times, in this world of science and technology and recent advancements like machine learning and artificial intelligence, clinicians and medical science are supported with better treatment assistance, increased efficiency and improved methodology in the detection of even the rarest tumour in the human body. In the field of oncology, the help of AI has proved promising results. Diagnosing by imaging and detecting gliomas, its grading can be done easily and accurately. This article focuses on recent advances and technologies in the field of AI and CNS Brain tumour detection. Rare and difficult tumours hard to detect and identify can now be seen and classified with the help of these newer technologies. Pre Intra and post-operative strategies can be planned accurately and most precisely with the help of AI. It is a vast concept that helps enhance various human cognitive abilities in wide ranges.Deep Learning, one of the types of ML, has proved effective in automating many time-consuming steps, including lesion detection and segmentation. AI has several features such as detection and classification, tumour molecular properties, cancer-linked genetics, discoveries of various drugs, prediction of treatment, its outcomes as well as survival, and continued trends in personalized medicine in CNS tumours such as GBM with poor prognosis. Artificial Intelligence is a vast concept that helps enhance various human cognitive abilities in wide ranges. This review focuses on the recent advances in AI and its use in oncology, specifically in CNS, detection, and assessment planning of the underlying cause. Promises and challenges of the same are discussed below.https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/21/e3sconf_icecs2024_04002.pdfartificial intelligencedeep learningmachine learningoncologycentral nervous systemneuroimaging
spellingShingle Zotey Vaishnavi
Ambad Ranjit
Lamture Yashwant Ramrao
Jha Rakesh Kumar
Artificial Intelligence- Oncology and Central Nervous System Tumour Detection
E3S Web of Conferences
artificial intelligence
deep learning
machine learning
oncology
central nervous system
neuroimaging
title Artificial Intelligence- Oncology and Central Nervous System Tumour Detection
title_full Artificial Intelligence- Oncology and Central Nervous System Tumour Detection
title_fullStr Artificial Intelligence- Oncology and Central Nervous System Tumour Detection
title_full_unstemmed Artificial Intelligence- Oncology and Central Nervous System Tumour Detection
title_short Artificial Intelligence- Oncology and Central Nervous System Tumour Detection
title_sort artificial intelligence oncology and central nervous system tumour detection
topic artificial intelligence
deep learning
machine learning
oncology
central nervous system
neuroimaging
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/21/e3sconf_icecs2024_04002.pdf
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AT jharakeshkumar artificialintelligenceoncologyandcentralnervoussystemtumourdetection