A Survey on Medical Image Segmentation Based on Deep Learning Techniques DOI Creative Commons

Jayashree Moorthy,

Usha Devi Gandhi

Big Data and Cognitive Computing, Год журнала: 2022, Номер 6(4), С. 117 - 117

Опубликована: Окт. 17, 2022

Deep learning techniques have rapidly become important as a preferred method for evaluating medical image segmentation. This survey analyses different contributions in the deep field, including major common issues published recent years, and also discusses fundamentals of concepts applicable to The study can be applied categorization, object recognition, segmentation, registration, other tasks. First, basic ideas techniques, applications, frameworks are introduced. that operate ideal applications briefly explained. paper indicates there is previous experience with class has been designed describe respond various challenges field analysis such low accuracy classification, segmentation resolution, poor enhancement. Aiming solve these present improve evolution challenges, we provide suggestions future research.

Язык: Английский

Stroke Risk Prediction with Machine Learning Techniques DOI Creative Commons
Ηλίας Δρίτσας, Μαρία Τρίγκα

Sensors, Год журнала: 2022, Номер 22(13), С. 4670 - 4670

Опубликована: Июнь 21, 2022

A stroke is caused when blood flow to a part of the brain stopped abruptly. Without supply, cells gradually die, and disability occurs depending on area affected. Early recognition symptoms can significantly carry valuable information for prediction promoting healthy life. In this research work, with aid machine learning (ML), several models are developed evaluated design robust framework long-term risk occurrence. The main contribution study stacking method that achieves high performance validated by various metrics, such as AUC, precision, recall, F-measure accuracy. experiment results showed classification outperforms other methods, an AUC 98.9%, F-measure, precision recall 97.4% accuracy 98%.

Язык: Английский

Процитировано

169

RETRACTED ARTICLE: Integration of Healthcare 4.0 and blockchain into secure cloud-based electronic health records systems DOI Open Access
Hemant B. Mahajan, Ameer Sardar Kwekha Rashid, Aparna A. Junnarkar

и другие.

Applied Nanoscience, Год журнала: 2022, Номер 13(3), С. 2329 - 2342

Опубликована: Фев. 4, 2022

Язык: Английский

Процитировано

161

Machine learning and deep learning approach for medical image analysis: diagnosis to detection DOI Open Access
Meghavi Rana, Megha Bhushan

Multimedia Tools and Applications, Год журнала: 2022, Номер 82(17), С. 26731 - 26769

Опубликована: Дек. 24, 2022

Язык: Английский

Процитировано

154

Intelligent metaphotonics empowered by machine learning DOI Creative Commons
Sergey Krasikov, Aaron D. Tranter, Andrey Bogdanov

и другие.

Opto-Electronic Advances, Год журнала: 2022, Номер 5(3), С. 210147 - 210147

Опубликована: Янв. 1, 2022

In the recent years, a dramatic boost of research is observed at junction photonics, machine learning and artificial intelligence. A new methodology can be applied to description variety photonic systems including optical waveguides, nanoantennas, metasurfaces. These novel approaches underpin fundamental principles light-matter interaction developed for smart design intelligent devices. Artificial intelligence machine learning penetrate rapidly into physics light, they provide effective tools study field metaphotonics driven by optically induced electric magnetic resonances.  Here we overview evaluation metaphotonics artificial present summary concepts with some specific examples demonstrated metasystems

Язык: Английский

Процитировано

136

Fish quality evaluation by sensor and machine learning: A mechanistic review DOI
Rehan Saeed, Huanhuan Feng, Xiang Wang

и другие.

Food Control, Год журнала: 2022, Номер 137, С. 108902 - 108902

Опубликована: Фев. 23, 2022

Язык: Английский

Процитировано

87

RETRACTED ARTICLE: 5G standards for the Industry 4.0 enabled communication systems using artificial intelligence: perspective of smart healthcare system DOI Open Access
Bilal Alhayani, Ameer Sardar Kwekha Rashid, Hemant B. Mahajan

и другие.

Applied Nanoscience, Год журнала: 2022, Номер 13(3), С. 1807 - 1817

Опубликована: Янв. 21, 2022

Язык: Английский

Процитировано

73

RETRACTED ARTICLE: A MobileNet-based CNN model with a novel fine-tuning mechanism for COVID-19 infection detection DOI Open Access
Yasin Kaya, Ercan Gürsoy

Soft Computing, Год журнала: 2023, Номер 27(9), С. 5521 - 5535

Опубликована: Янв. 4, 2023

Язык: Английский

Процитировано

72

Automated detection and forecasting of COVID-19 using deep learning techniques: A review DOI
Afshin Shoeibi, Marjane Khodatars, Mahboobeh Jafari

и другие.

Neurocomputing, Год журнала: 2024, Номер 577, С. 127317 - 127317

Опубликована: Янв. 26, 2024

Язык: Английский

Процитировано

55

Review on the Evaluation and Development of Artificial Intelligence for COVID-19 Containment DOI Creative Commons
Md. Mahadi Hasan, Muhammad Usama Islam, Muhammad Jafar Sadeq

и другие.

Sensors, Год журнала: 2023, Номер 23(1), С. 527 - 527

Опубликована: Янв. 3, 2023

Artificial intelligence has significantly enhanced the research paradigm and spectrum with a substantiated promise of continuous applicability in real world domain. intelligence, driving force current technological revolution, been used many frontiers, including education, security, gaming, finance, robotics, autonomous systems, entertainment, most importantly healthcare sector. With rise COVID-19 pandemic, several prediction detection methods using artificial have employed to understand, forecast, handle, curtail ensuing threats. In this study, recent related publications, methodologies medical reports were investigated purpose studying intelligence's role pandemic. This study presents comprehensive review specific attention machine learning, deep image processing, object detection, segmentation, few-shot learning studies that utilized tasks COVID-19. particular, genetic analysis, clinical data sound biomedical classification, socio-demographic anomaly health monitoring, personal protective equipment (PPE) observation, social control, patients' mortality risk approaches forecast threatening factors demonstrates artificial-intelligence-based algorithms integrated into Internet Things wearable devices quite effective efficient forecasting insights which actionable through wide usage. The results produced by prove is promising arena can be applied for disease prognosis, forecasting, drug discovery, development sector on global scale. We indeed played important helping fight against COVID-19, insightful knowledge provided here could extremely beneficial practitioners experts domain implement systems curbing next pandemic or disaster.

Язык: Английский

Процитировано

46

RETRACTED ARTICLE: Deepfake detection using rationale-augmented convolutional neural network DOI
Saadaldeen Rashid Ahmed, Emrullah Sonuç

Applied Nanoscience, Год журнала: 2021, Номер 13(2), С. 1485 - 1493

Опубликована: Сен. 13, 2021

Язык: Английский

Процитировано

95