Mono-Rectangular Core Photonic Crystal Fiber (MRC-PCF) for Skin and Blood Cancer Detection

Eid, Mahmoud M. A.; Rashed, Ahmed Nabih Zaki; Bulbul, Abdullah Al-Mamun; Podder, Etu

doi:10.1007/s11468-020-01334-0

Cited by 132 publications

(27 citation statements)

References 34 publications

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“…Cancer is the abandoned outgrowth of abnormal cells that may spread to different parts of the human body 1 . Currently, it is one of the leading causes of death in the world.…”

Section: Introductionmentioning

confidence: 99%

Blood cancer prediction using leukemia microarray gene data and hybrid logistic vector trees model

Rupapara

Rustam

Aljedaani

et al. 2022

Sci Rep

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Blood cancer has been a growing concern during the last decade and requires early diagnosis to start proper treatment. The diagnosis process is costly and time-consuming involving medical experts and several tests. Thus, an automatic diagnosis system for its accurate prediction is of significant importance. Diagnosis of blood cancer using leukemia microarray gene data and machine learning approach has become an important medical research today. Despite research efforts, desired accuracy and efficiency necessitate further enhancements. This study proposes an approach for blood cancer disease prediction using the supervised machine learning approach. For the current study, the leukemia microarray gene dataset containing 22,283 genes, is used. ADASYN resampling and Chi-squared (Chi2) features selection techniques are used to resolve imbalanced and high-dimensional dataset problems. ADASYN generates artificial data to make the dataset balanced for each target class, and Chi2 selects the best features out of 22,283 to train learning models. For classification, a hybrid logistics vector trees classifier (LVTrees) is proposed which utilizes logistic regression, support vector classifier, and extra tree classifier. Besides extensive experiments on the datasets, performance comparison with the state-of-the-art methods has been made for determining the significance of the proposed approach. LVTrees outperform all other models with ADASYN and Chi2 techniques with a significant 100% accuracy. Further, a statistical significance T-test is also performed to show the efficacy of the proposed approach. Results using k-fold cross-validation prove the supremacy of the proposed model.

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“…Cancer is the abandoned outgrowth of abnormal cells that may spread to different parts of the human body 1 . Currently, it is one of the leading causes of death in the world.…”

Section: Introductionmentioning

confidence: 99%

Blood cancer prediction using leukemia microarray gene data and hybrid logistic vector trees model

Rupapara

Rustam

Aljedaani

et al. 2022

Sci Rep

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“…The pH measurement sensitivity was 1.21459 with good linearity of 0.97761. In addition to the above experimental demonstrations, several groups performed detailed numerical investigations for different novel sensing configurations, such as D-shaped photonic crystal fiber (PCF), mono-rectangular core PCF, twin-core PCF, etc., to enhance the sensitivity, improve the figure of merit, and provide the user-friendly interface [ 50 , 56 , 57 , 58 , 59 , 60 ].…”

Section: Fiber Optic Biosensorsmentioning

confidence: 99%

Optical Fiber, Nanomaterial, and THz-Metasurface-Mediated Nano-Biosensors: A Review

et al. 2022

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The increasing use of nanomaterials and scalable, high-yield nanofabrication process are revolutionizing the development of novel biosensors. Over the past decades, researches on nanotechnology-mediated biosensing have been on the forefront due to their potential application in healthcare, pharmaceutical, cell diagnosis, drug delivery, and water and air quality monitoring. The advancement of nanoscale science relies on a better understanding of theory, manufacturing and fabrication practices, and the application specific methods. The topology and tunable properties of nanoparticles, a part of nanoscale science, can be changed by different manufacturing processes, which separate them from their bulk counterparts. In the recent past, different nanostructures, such as nanosphere, nanorods, nanofiber, core–shell nanoparticles, nanotubes, and thin films, have been exploited to enhance the detectability of labelled or label-free biological molecules with a high accuracy. Furthermore, these engineered-materials-associated transducing devices, e.g., optical waveguides and metasurface-based scattering media, widened the horizon of biosensors over a broad wavelength range from deep-ultraviolet to far-infrared. This review provides a comprehensive overview of the major scientific achievements in nano-biosensors based on optical fiber, nanomaterials and terahertz-domain metasurface-based refractometric, labelled and label-free nano-biosensors.

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“…The proposed model affords the relative sensitivity of around 98% and we have also numerically investigated several significant optical properties, for instance, confinement loss, effective area, EML, etc. The proposed model offers better sensing characteristics than some of the recently proposed sensor models (Terahertz sensor) in sensing applications [12][13][14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 97%

Novel Hollow Octagonal Core Photonic Crystal Fiber (PCF) based Cholesterol Sensor

Bulbul

Podder

Faragallah

et al. 2021

Preprint

Self Cite

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Cholesterol, also known as the pulpy fat of human body, may cause the body vulnerable to heart malady by filling blood-vessel with fatty substances. This urges a precise, simple, and effective method of cholesterol detection. Considering this, a novel hollow equilateral-octagon core PCF model has been presented as a cholesterol sensor. The sensor is modeled and simulated using finite element method (FEM). Multiple performance metrics suggests the effectiveness of the proposed sensor model. The relative sensitivity attained for the model is 92.34% at optimum frequency (OF), 3.6THz. Besides, the model shows ultra-lower confinement loss of 3.77×10− 18cm−1 at OF along with standard values for other performance metrics. In addition, the feasible implementation of the model by exercising existing fabrication strategies ensures the practicability of the proposed sensor.

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Mono-Rectangular Core Photonic Crystal Fiber (MRC-PCF) for Skin and Blood Cancer Detection

Cited by 132 publications

References 34 publications

Blood cancer prediction using leukemia microarray gene data and hybrid logistic vector trees model

Blood cancer prediction using leukemia microarray gene data and hybrid logistic vector trees model

Optical Fiber, Nanomaterial, and THz-Metasurface-Mediated Nano-Biosensors: A Review

Novel Hollow Octagonal Core Photonic Crystal Fiber (PCF) based Cholesterol Sensor

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