Medical Image Processing: Detection and Prediction of PCOS –A Systematic Literature Review

Pulluparambil, Siji Jose; Bhat, Subrahmanya

doi:10.5281/zenodo.5782763

Cited by 1 publication

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“…The best performing demonstrate was SVM with classification exactness of Pacc = 81.3% (affectability Psen = 87.4% and specificity of Pspe = 80.9%) 3 Eskofier et al [19] 2016 Proposed a profound learning calculation called Convolutional Neural Arrange (CNN), which focuses at gaining features from a banner removed in the midst of the singular's test by suggests of a canny compose made out of a course of action of sensors that can remove information from deciphered elements. 4 Petersen, B. S., et al [8] 2017…”

Section: Related Work On Detection and Prediction Of Neurodegenrative...mentioning

confidence: 99%

“…It helps scientists and medical care specialists to stagger on the secret information. Furthermore, it assists clinical specialists for concentrating on the types of affliction accurately after which with assisting with offering cure better [4]. In this review paper we have complete an effort to use deep learning algorithms to detect and predict Parkinson's disease by analyzing handwriting of a individual suffering from Parkinson's disease.…”

Section: Introductionmentioning

confidence: 99%

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Design and Development of Efficient Model to Predict Neurodegenerative Disorders Using Advanced LSTM: A Review of Literature

Devi

2022

IJCSBE

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Purpose: A continuous Nervous system illness that influences development is known as neurodegenerative sickness. Side effects show up continuously, and may start with a scarcely distinguishable quake in just a single hand. Quakes are normal, but they are frequently joined by firmness or eased back versatility. The emphasis is on Parkinson's infection specifically (PD). The signs and results of Parkinson's contamination shift starting with one individual then onto the next. Early reprimand markers could be subtle and go unnoticed. Regardless, when aftereffects start to influence the different sides of your body, secondary effects normally jump on single side of your body and decay on that side. Parkinson's illness is brought about by the demise of nerve cells in the substantia nigra, a portion of the cerebrum. The exactness of a few fake brain network approaches, for example, Convolutional Neural Network, Recurrent Neural Network, Long-Short term Memory network have been concentrated on to analyze Parkinson's illnesses. This record inspects a synopsis of a portion of the examination and concentrates on that have been directed in the field of clinical diagnostics. In light of the audit, research holes are featured, as well as examination needs for future review. Approach: A thorough study on the algorithms used in analysis of handwritten and vocal to distinguish and anticipate Parkinson's illness. Findings: The review showed that the majority of the AI and deep learning strategy can order neurodegenerative illness in view of vocal, transcribed and walk investigation in light of the clinical datasets. The new crossover philosophy proposed will be more exact as the model will actually want to foresee and distinguish neurodegenerative sickness in view of eye development. Originality: The sort of information expected for forecast and discovery framework are considered and the design and portrayal outline of a proposed model are incorporated. Paper Type: Literature Review.

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Section: Related Work On Detection and Prediction Of Neurodegenrative...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design and Development of Efficient Model to Predict Neurodegenerative Disorders Using Advanced LSTM: A Review of Literature

Devi

2022

IJCSBE

View full text Add to dashboard Cite

show abstract

Medical Image Processing: Detection and Prediction of PCOS –A Systematic Literature Review

Cited by 1 publication

References 0 publications

Design and Development of Efficient Model to Predict Neurodegenerative Disorders Using Advanced LSTM: A Review of Literature

Design and Development of Efficient Model to Predict Neurodegenerative Disorders Using Advanced LSTM: A Review of Literature

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