From tedious to targeted: Optimizing oral cancer research with Consensus AI

Barriers which include subjective biases, overabundance of data, and budget limitations impede oral cancer research. Conventional techniques consume an extensive amount of time, are biased, and have limitations. Consensus AI, on the other hand, presents a viable alternative by effectively sorting th...

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Main Authors: Ajinkya M. Pawar, Rajiv Desai, Bhagyashree Thakur
Format: Article
Language:English
Published: Elsevier 2024-06-01
Series:Oral Oncology Reports
Online Access:http://www.sciencedirect.com/science/article/pii/S2772906024002292
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author Ajinkya M. Pawar
Rajiv Desai
Bhagyashree Thakur
author_facet Ajinkya M. Pawar
Rajiv Desai
Bhagyashree Thakur
author_sort Ajinkya M. Pawar
collection DOAJ
description Barriers which include subjective biases, overabundance of data, and budget limitations impede oral cancer research. Conventional techniques consume an extensive amount of time, are biased, and have limitations. Consensus AI, on the other hand, presents a viable alternative by effectively sorting through enormous datasets by utilizing several AI algorithms. Consensus AI reduces biases, increases efficiency, and improves article selection dependability by merging a variety of AI models. Research on oral cancer may be able to make more accurate predictions and get deeper insights because to its capacity to combine different data sources and apply ensemble learning. The editorial explore the role of Consensus AI in method optimization.
format Article
id doaj-art-b1f8995889884406988c7d26f0f75f4e
institution Kabale University
issn 2772-9060
language English
publishDate 2024-06-01
publisher Elsevier
record_format Article
series Oral Oncology Reports
spelling doaj-art-b1f8995889884406988c7d26f0f75f4e2025-01-09T06:16:02ZengElsevierOral Oncology Reports2772-90602024-06-0110100383From tedious to targeted: Optimizing oral cancer research with Consensus AIAjinkya M. Pawar0Rajiv Desai1Bhagyashree Thakur2Corresponding author.; Department of Conservative Dentistry and Endodontics, Nair Hospital Dental College, Mumbai, Maharashtra, IndiaDepartment of Oral Pathology and Microbiology, Nair Hospital Dental College, Mumbai, Maharashtra, IndiaDepartment of Dentistry, Division of District Early Intervention Centre, Thane Civil Hospital, 400601, Thane, IndiaBarriers which include subjective biases, overabundance of data, and budget limitations impede oral cancer research. Conventional techniques consume an extensive amount of time, are biased, and have limitations. Consensus AI, on the other hand, presents a viable alternative by effectively sorting through enormous datasets by utilizing several AI algorithms. Consensus AI reduces biases, increases efficiency, and improves article selection dependability by merging a variety of AI models. Research on oral cancer may be able to make more accurate predictions and get deeper insights because to its capacity to combine different data sources and apply ensemble learning. The editorial explore the role of Consensus AI in method optimization.http://www.sciencedirect.com/science/article/pii/S2772906024002292
spellingShingle Ajinkya M. Pawar
Rajiv Desai
Bhagyashree Thakur
From tedious to targeted: Optimizing oral cancer research with Consensus AI
Oral Oncology Reports
title From tedious to targeted: Optimizing oral cancer research with Consensus AI
title_full From tedious to targeted: Optimizing oral cancer research with Consensus AI
title_fullStr From tedious to targeted: Optimizing oral cancer research with Consensus AI
title_full_unstemmed From tedious to targeted: Optimizing oral cancer research with Consensus AI
title_short From tedious to targeted: Optimizing oral cancer research with Consensus AI
title_sort from tedious to targeted optimizing oral cancer research with consensus ai
url http://www.sciencedirect.com/science/article/pii/S2772906024002292
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