Objective and Impact *** use deep learning models to classify cervix images—collected with a low-cost,portable Pocket colposcope—with biopsy-confirmed high-grade precancer and *** boost classification performance on...
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Objective and Impact *** use deep learning models to classify cervix images—collected with a low-cost,portable Pocket colposcope—with biopsy-confirmed high-grade precancer and *** boost classification performance on a screened-positive population by using a class-balanced loss and incorporating green-light colposcopy image pairs,which come at no additional cost to the *** the majority of the 300,000 annual deaths due to cervical cancer occur in countries with low-or middle-Human Development Indices,an automated classification algorithm could overcome limitations caused by the low prevalence of trained professionals and diagnostic variability in provider visual *** dataset consists of cervical images(n=1,760)from 880 patient *** optimizing the network architecture and incorporating a weighted loss function,we explore two methods of incorporating green light image pairs into the network to boost the classification performance and sensitivity of our model on a test *** achieve an area under the receiver-operator characteristic curve,sensitivity,and specificity of 0.87,75%,and 88%,*** addition of the class-balanced loss and green light cervical contrast to a Resnet-18 backbone results in a 2.5 times improvement in *** methodology,which has already been tested on a prescreened population,can boost classification performance and,in the future,be coupled with Pap smear or HPV triaging,thereby broadening access to early detection of precursor lesions before they advance to cancer.
Globalization has revolutionized how different entities are distributed across locations interconnect and collaborated to enhance the availability of different services even at remote areas. Supply chains have played ...
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Globalization has revolutionized how different entities are distributed across locations interconnect and collaborated to enhance the availability of different services even at remote areas. Supply chains have played an important role in expanding business operations globally and at the same time increasing operational efficiency and reducing costs. Pharmaceutical Supply Chain (PSC) is one of the important aspects of healthcare which is vital for resource acquisition, manufacturing, and distribution of prescription drugs from the manufacturer site to patients. "Five rights of medication” is the main motto of the PSC which ensures the delivery of the right medicine to the right patient, at the right time, in the right doses, and through the appropriate route. Following this principle achieves patient safety in the healthcare system. However, as the number of entities participating in the PSC is large, which are geographically distributed and interact in complex ways makes the PSC more abstract and causes adversaries to introduce counterfeit medicines into the system. Developing a transparent PSC with no information fragmentation is very much needed for efficient track and trace along with easy identification and avoidance of counterfeit drugs. The current paper proposes one such architecture that is integrated with Blockchain, Distributed File Storage System, and Barcode technologies to provide a secure Barcode mechanism for addressing such tracking and tracing issues in the pharmaceutical supply chain. The novel product serialization mechanism proposed in PharmaChain 3.0 also ensures accurate identification, capture, and sharing of information about the drugs manufactured between these participating entities without the use of centralized entities and removing blind parties. The current system is designed to efficiently capture both Pedigree and T3 information of drugs in order to comply with regulations like Drug Supply Chain Security Act (DSCSA) and Prescription D
Brain tumor significantly impacts the quality of life and changes everything for a patient and their loved *** a brain tumor usually begins with magnetic resonance imaging(MRI).The manual brain tumor diagnosis from th...
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Brain tumor significantly impacts the quality of life and changes everything for a patient and their loved *** a brain tumor usually begins with magnetic resonance imaging(MRI).The manual brain tumor diagnosis from the MRO images always requires an expert ***,this process is time-consuming and ***,a computerized technique is required for brain tumor detection in MRI *** the MRI,a novel mechanism of the three-dimensional(3D)Kronecker convolution feature pyramid(KCFP)is used to segment brain tumors,resolving the pixel loss and weak processing of multi-scale lesions.A single dilation rate was replaced with the 3D Kronecker convolution,while local feature learning was performed using the 3D Feature Selection(3DFSC).A 3D KCFP was added at the end of 3DFSC to resolve weak processing of multi-scale lesions,yielding efficient segmentation of brain tumors of different sizes.A 3D connected component analysis with a global threshold was used as a post-processing *** standard Multimodal Brain Tumor Segmentation 2020 dataset was used for model *** 3D KCFP model performed exceptionally well compared to other benchmark schemes with a dice similarity coefficient of 0.90,0.80,and 0.84 for the whole tumor,enhancing tumor,and tumor core,***,the proposed model was efficient in brain tumor segmentation,which may facilitate medical practitioners for an appropriate diagnosis for future treatment planning.
Large-scale pre-training has shown remarkable performance in building open-domain dialogue ***,previous works mainly focus on showing and evaluating the conversational performance of the released dialogue model,ignori...
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Large-scale pre-training has shown remarkable performance in building open-domain dialogue ***,previous works mainly focus on showing and evaluating the conversational performance of the released dialogue model,ignoring the discussion of some key factors towards a powerful human-like chatbot,especially in Chinese *** this paper,we conduct extensive experiments to investigate these under-explored factors,including data quality control,model architecture designs,training approaches,and decoding *** propose EVA2.0,a large-scale pre-trained open-domain Chinese dialogue model with 2.8 billion parameters,and will make our models and codes publicly *** and human evaluations show that EVA2.0 significantly outperforms other open-source *** also discuss the limitations of this work by presenting some failure cases and pose some future research directions on large-scale Chinese open-domain dialogue systems.
A super-resolution electromagnetic inversion scheme is proposed for brain stroke detection. The scheme operates in two stages: (i) A quantitative Gauss-Newton method with Tikhonov regularization and frequency-hopping ...
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In the medical profession,recent technological advancements play an essential role in the early detection and categorization of many diseases that cause *** technique rising on daily basis for detecting illness in mag...
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In the medical profession,recent technological advancements play an essential role in the early detection and categorization of many diseases that cause *** technique rising on daily basis for detecting illness in magnetic resonance through pictures is the inspection of ***(computerized)illness detection in medical imaging has found you the emergent region in several medical diagnostic *** diseases that cause death need to be identified through such techniques and technologies to overcome the mortality *** brain tumor is one of the most common causes of *** have already proposed various models for the classification and detection of tumors,each with its strengths and weaknesses,but there is still a need to improve the classification process with improved effi***,in this study,we give an in-depth analysis of six distinct machine learning(ML)algorithms,including Random Forest(RF),Naïve Bayes(NB),Neural Networks(NN),CN2 Rule Induction(CN2),Support Vector Machine(SVM),and Decision Tree(Tree),to address this gap in improving *** the Kaggle dataset,these strategies are tested using classification accuracy,the area under the Receiver Operating Characteristic(ROC)curve,precision,recall,and F1 Score(F1).The training and testing process is strengthened by using a 10-fold cross-validation *** results show that SVM outperforms other algorithms,with 95.3%accuracy.
In recent years,the exponential proliferation of smart devices with their intelligent applications poses severe challenges on conventional cellular *** challenges can be potentially overcome by integrating communicati...
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In recent years,the exponential proliferation of smart devices with their intelligent applications poses severe challenges on conventional cellular *** challenges can be potentially overcome by integrating communication,computing,caching,and control(i4C)*** this survey,we first give a snapshot of different aspects of the i4C,comprising background,motivation,leading technological enablers,potential applications,and use ***,we describe different models of communication,computing,caching,and control(4C)to lay the foundation of the integration *** review current stateof-the-art research efforts related to the i4C,focusing on recent trends of both conventional and artificial intelligence(AI)-based integration *** also highlight the need for intelligence in resources ***,we discuss the integration of sensing and communication(ISAC)and classify the integration approaches into various ***,we propose open challenges and present future research directions for beyond 5G networks,such as 6G.
This paper proposes an inverse design method for frequency selective surfaces (FSS) based on an equivalent circuit model (ECM) and output space mapping (OSM) technique. The method establishes an OSM enhanced ECM model...
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In the wake of disasters, rapid and efficient search and rescue operations are essential. Unmanned aerial vehicles (UAVs) have become instrumental in such scenarios, providing real-time video streaming that can be use...
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