Implementation of blockchain technology using extended CNN for lung cancer prediction

Pawar, A.B.; Jawale, M.A.; William, P.; Chhabra, G.S.; Rakshe, Dhananjay S.; Korde, Sachin K.; Marriwala, Nikhil

doi:10.1016/j.measen.2022.100530

Cited by 38 publications

(5 citation statements)

References 12 publications

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“…Blockchain innovation enjoys the benefits of the lowest exchange costs, solid straightforwardness, and the highest securities. Normal issues like a significant expense, low effectiveness, and low information stockpiling security in the normalized data set give groundbreaking thoughts [13,14]. Blockchain is a carefully designed, full history information base stockpiling innovation that ordinarily utilizes highlight direct innovation to coordinate every hub.…”

Section: Blockchain-based Crn Security Techniquementioning

confidence: 99%

An Analytical Model for Dynamic Spectrum Sensing in Cognitive Radio Networks Using Blockchain Management

Marriwala,

Panda,

Kamalanathan

et al. 2024

RAiSE-2023

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Section: Blockchain-based Crn Security Techniquementioning

confidence: 99%

An Analytical Model for Dynamic Spectrum Sensing in Cognitive Radio Networks Using Blockchain Management

Marriwala,

Panda,

Kamalanathan

et al. 2024

RAiSE-2023

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“…Moxifloxacin or gatifloxacin was functionalized with polydopamine, and the conjugates demonstrated enhanced Acinetobacter strain, pseudomonas, and Klebsiella pneumonia biofilms were all affected by the antibiofilm activity. A synergistic action was evident since the improved antibiofilm activity was much higher than that of the antibiotic alone or of polymerized AgNPs [17]. In [18], developed a new hydrogel with exceptional bactericidal activity by effectively creating galactic acid function AgNPs (GA-AgNPs) embedding into the network design of a biocompatible polysaccharide after utilizing a one-pot method.…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of Silver Nanoparticles as Carriers of Drug Delivery System

Pawar,

Korde,

Rakshe

et al. 2023

J. Nano- Electron. Phys.

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Nanotechnology has advanced significantly over the last decade and has found several uses in fields as diverse as medical, pharmaceuticals, microelectronics, aerospace, and the food industry. The use of nanoparticle (NP) drug carriers has been investigated, and this method offers several benefits. Some of these benefits include the controlled and targeted release of loaded or coupled drugs, as well as an improvement in the bioavailability of the drug. However, they also have certain drawbacks, such as their in vivo toxicity, which affects all organs, including the healthy ones, and the overall benefit of the illness therapy, which might be insignificant or limited. Due to their unique physical, chemical, and optical characteristics, AgNP have attracted a lot of attention in recent years. These NP have several potential uses, including drug delivery. Methods that get around these problems are crucial since traditional cancer chemotherapy has several drawbacks, including limited bioavailability and the need for high dosages that have side effects. The study examines AgNP as a drug delivery system for the treatment of cancer. The paper also examines the most recent developments in the use of AgNP for the delivery of anticancer medications and their impact on antitumor effects. It is also observed that silver nano particles can characterize their physicochemical properties and determine the presence of any potential toxicity.

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“…Another study on lung cancer utilized Internet of Things (IoT) technology in addition to CT images. Data from both CT and wearable technologies were combined, processed through an Extended Convolutional Neural Network (ECNN), resulting in an accuracy of 96.8% [19]. Haznedar and Simsek analyzed lung and renal cell cancer RNA-Seq data sets from the Cancer Genome Atlas (TCGA) using both classical machine learning methods and deep learning techniques.…”

Section: Introductionmentioning

confidence: 99%

Detection of Lung Cancer Cells Using Deep Learning Methods

Genç,

Akar

2024

Bitlis Eren Üniversitesi Fen Bilimleri Dergisi

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Lung cancer stands out as a high mortality, fatal disease worldwide. Early diagnosis is crucial for effective treatment of this disease; however, treatment options can be limited when it is often diagnosed in advanced stages. This study examines the role of artificial intelligence (AI) techniques in early diagnosis of lung cancer and emphasizes the advantages it provides. Particularly, the ability of deep learning algorithms to extract meaningful features from complex datasets indicates significant potential for detecting early stages of lung cancer. In this context, it is anticipated that AI-supported diagnostic systems have the potential to significantly improve lung cancer diagnostic methods by reducing the workload of radiologists and increasing accuracy rates. In this study, a total of 6 datasets were obtained by applying Gabor filter and Histogram Equalization+CLAHE filter to original datasets. The results obtained in the diagnosis of lung cancer using Convolutional Neural Networks (CNN) and YOLO algorithms are evaluated in two different categories. One of these categories is the investigation of the effect of image preprocessing methods. The other is the investigation of the effect of dataset partitioning into training, testing, and validation on success. According to the results obtained, the highest success rate in terms of F1 Score for the CNN model was achieved in both dataset partitioning (70%-20%-10% and 60%-20%-20%) with the datasets subjected to Histogram Equalization+CLAHE filter. It was obtained as 99%. For the YOLO model, the highest success rate was determined as 96% F1 Score with the same preprocessing technique and dataset partition. The effect of image preprocessing and dataset partitioning on success is not as high in the YOLO model as it is in the CNN model.

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Implementation of blockchain technology using extended CNN for lung cancer prediction

Cited by 38 publications

References 12 publications

An Analytical Model for Dynamic Spectrum Sensing in Cognitive Radio Networks Using Blockchain Management

An Analytical Model for Dynamic Spectrum Sensing in Cognitive Radio Networks Using Blockchain Management

Analysis of Silver Nanoparticles as Carriers of Drug Delivery System

Detection of Lung Cancer Cells Using Deep Learning Methods

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