Article: A review on speech organ diseases and cancer detection using artificial intelligence Journal: International Journal of Computational Biology and Drug Design (IJCBDD) 2023 Vol.15 No.4 pp.336 - 356 Abstract: Cancer is an abnormal expansion of tissues and is among the common illnesses in India, accounting for 0.3 fatalities each year. It can appear in any way and is incredibly challenging to spot in its early phases. Thus, Speech organ-related cancer detection using image processing-based techniques and ML is a challenging field in the medical domain, which involves early detection and diagnosis of cancer. This research defines the methods, algorithms, and datasets used by the existing researchers on speech organ diseases. The results from the state-of-the-art works are evaluated by accuracy, false-positive rate, and area under the ROC curve (AUC). The merits and demerits of these approaches are examined, which paves the way for future research in reducing the death rate of patients. The literature studies motivate us to develop early detection of cancer of all speech organs with resources of mobile-related applications to use in real-time will be our future vision. Thus, 60-80% of all speech-related organ infections or cancerous cases can be detected at early stages by this one mobile-related application, which will be beneficial for people in reducing the death rate of patients. Inderscience Publishers - linking academia, business and industry through research

Title: A review on speech organ diseases and cancer detection using artificial intelligence

Authors: M. Swathi; Rajeshkannan Regunathan; Suresh Kumar Nagarajan

Addresses: School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, 632014, Tamil Nadu, India ' School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, 632014, Tamil Nadu, India ' School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, 632014, Tamil Nadu, India

Abstract: Cancer is an abnormal expansion of tissues and is among the common illnesses in India, accounting for 0.3 fatalities each year. It can appear in any way and is incredibly challenging to spot in its early phases. Thus, Speech organ-related cancer detection using image processing-based techniques and ML is a challenging field in the medical domain, which involves early detection and diagnosis of cancer. This research defines the methods, algorithms, and datasets used by the existing researchers on speech organ diseases. The results from the state-of-the-art works are evaluated by accuracy, false-positive rate, and area under the ROC curve (AUC). The merits and demerits of these approaches are examined, which paves the way for future research in reducing the death rate of patients. The literature studies motivate us to develop early detection of cancer of all speech organs with resources of mobile-related applications to use in real-time will be our future vision. Thus, 60-80% of all speech-related organ infections or cancerous cases can be detected at early stages by this one mobile-related application, which will be beneficial for people in reducing the death rate of patients.

Keywords: deep learning; larynx; pharynx; throat cancer; tonsillitis; oral cavity; voice disorders; ROC curve; speech organs.

DOI: 10.1504/IJCBDD.2023.130324

International Journal of Computational Biology and Drug Design, 2023 Vol.15 No.4, pp.336 - 356

Received: 16 Aug 2022
Accepted: 11 Nov 2022
Published online: 17 Apr 2023 *

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Title: A review on speech organ diseases and cancer detection using artificial intelligence

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