1,248 results match your criteria era big


OTNet: A CNN Method Based on Hierarchical Attention Maps for Grading Arteriosclerosis of Fundus Images with Small Samples.

Interdiscip Sci 2021 Sep 18. Epub 2021 Sep 18.

China Aerospace Science and Industry Corporation, Beijing, China.

The severity of fundus arteriosclerosis can be determined and divided into four grades according to fundus images. Automatically grading of the fundus arteriosclerosis is helpful in clinical practices, so this paper proposes a convolutional neural network (CNN) method based on hierarchical attention maps to solve the automatic grading problem. First, we use the retinal vessel segmentation model to separate the important vascular region and the non-vascular background region from the fundus image and obtain two attention maps. Read More

View Article and Full-Text PDF
September 2021

"Big Three" Infectious Diseases: Tuberculosis, Malaria and HIV/AIDS.

Curr Top Med Chem 2021 Sep 16. Epub 2021 Sep 16.

Department of Chemistry, Pondicherry University, Kalapet, Puducherry- 605014. India.

Infectious diseases have been evolving and re-evolving over the ages and causing immense misery to humans. Among them, some have been prevented and eradicated, but few are still threatening the modern era since their origin. The majority of these infectious diseases are poverty-driven, hence highly prevalent in the lower-income and mid-income countries of Africa and Asia. Read More

View Article and Full-Text PDF
September 2021

Privacy and artificial intelligence: challenges for protecting health information in a new era.

Authors:
Blake Murdoch

BMC Med Ethics 2021 Sep 15;22(1):122. Epub 2021 Sep 15.

Health Law Institute, Faculty of Law, University of Alberta, Edmonton, AB, T6G 2H5, Canada.

Background: Advances in healthcare artificial intelligence (AI) are occurring rapidly and there is a growing discussion about managing its development. Many AI technologies end up owned and controlled by private entities. The nature of the implementation of AI could mean such corporations, clinics and public bodies will have a greater than typical role in obtaining, utilizing and protecting patient health information. Read More

View Article and Full-Text PDF
September 2021

Benchmarking of Data-Driven Causality Discovery Approaches in the Interactions of Arctic Sea Ice and Atmosphere.

Front Big Data 2021 24;4:642182. Epub 2021 Aug 24.

Department of Information Systems, University of Maryland, Baltimore, MD, United States.

The Arctic sea ice has retreated rapidly in the past few decades, which is believed to be driven by various dynamic and thermodynamic processes in the atmosphere. The newly open water resulted from sea ice decline in turn exerts large influence on the atmosphere. Therefore, this study aims to investigate the causality between multiple atmospheric processes and sea ice variations using three distinct data-driven causality approaches that have been proposed recently: Temporal Causality Discovery Framework Non-combinatorial Optimization Trace Exponential and Augmented lagrangian for Structure learning (NOTEARS) and Directed Acyclic Graph-Graph Neural Networks (DAG-GNN). Read More

View Article and Full-Text PDF

Utilizing machine learning to improve clinical trial design for acute respiratory distress syndrome.

NPJ Digit Med 2021 Sep 9;4(1):133. Epub 2021 Sep 9.

Philips Research North America, Cambridge, MA, USA.

Heterogeneous patient populations, complex pharmacology and low recruitment rates in the Intensive Care Unit (ICU) have led to the failure of many clinical trials. Recently, machine learning (ML) emerged as a new technology to process and identify big data relationships, enabling a new era in clinical trial design. In this study, we designed a ML model for predictively stratifying acute respiratory distress syndrome (ARDS) patients, ultimately reducing the required number of patients by increasing statistical power through cohort homogeneity. Read More

View Article and Full-Text PDF
September 2021

Big Data for Biomedical Education with a Focus on the COVID-19 Era: An Integrative Review of the Literature.

Int J Environ Res Public Health 2021 08 26;18(17). Epub 2021 Aug 26.

Laboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada.

Medical education refers to education and training delivered to medical students in order to become a practitioner. In recent decades, medicine has been radically transformed by scientific and computational/digital advances-including the introduction of new information and communication technologies, the discovery of DNA, and the birth of genomics and post-genomics super-specialties (transcriptomics, proteomics, interactomics, and metabolomics/metabonomics, among others)-which contribute to the generation of an unprecedented amount of data, so-called 'big data'. While these are well-studied in fields such as medical research and methodology, translational medicine, and clinical practice, they remain overlooked and understudied in the field of medical education. Read More

View Article and Full-Text PDF

Spatial Pattern Evaluation of Rural Tourism via the Multifactor-Weighted Neural Network Model in the Big Data Era.

Comput Intell Neurosci 2021 27;2021:5845545. Epub 2021 Aug 27.

School of Culture and Tourism, Ningxia University, Zhongwei 755000, China.

The exploration of the evaluation effect of rural tourism spatial pattern based on the multifactor-weighted neural network model in the era of big data aims to optimize the spatial layout of rural tourist attractions. There are plenty of problems such as improper site selection, layout dispersion, and market competition disorder of rural tourism caused by insufficient consideration of planning and tourist market. Hence, the multifactor model after simple weighting is combined with the neural network to construct a spatiotemporal convolution neural network model based on multifactor weighting here to solve these problems. Read More

View Article and Full-Text PDF
September 2021

Preparing for medical education after the COVID-19 pandemic: insightology in medicine.

Authors:
Yon Ho Choe

Korean J Med Educ 2021 Sep 27;33(3):163-170. Epub 2021 Aug 27.

Department of Pediatrics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.

It is necessary to reflect on the question, "How to prepare for medical education after coronavirus disease 2019 (COVID-19)?" Although we are preparing for the era of Education 4.0 in line with the 4th industrial revolution of artificial intelligence and big data, most measures are focused on the methodologies of transferring knowledge; essential innovation is not being addressed. What is fundamentally needed in medicine is insightful intelligence that can see the invisible. Read More

View Article and Full-Text PDF
September 2021

A Policy-Driven Approach to Secure Extraction of COVID-19 Data From Research Papers.

Front Big Data 2021 12;4:701966. Epub 2021 Aug 12.

IS Department, University of Maryland Baltimore County, Baltimore, MD, United States.

The entire scientific and academic community has been mobilized to gain a better understanding of the COVID-19 disease and its impact on humanity. Most research related to COVID-19 needs to analyze large amounts of data in very little time. This urgency has made Big Data Analysis, and related questions around the privacy and security of the data, an extremely important part of research in the COVID-19 era. Read More

View Article and Full-Text PDF

Research on Intelligent Solution of Service Industry Supply Chain Network Optimization Based on Genetic Algorithm.

Authors:
Yixin Zhou Zhen Guo

J Healthc Eng 2021 19;2021:9429872. Epub 2021 Aug 19.

School of Economics, Harbin University of Commerce, Harbin 150000, Heilongjiang, China.

With the advent of the era of big data (BD), people"s living standards and lifestyle have been greatly changed, and people's requirements for the service level of the service industry are becoming higher and higher. The personalized needs of customers and private customization have become the hot issues of current research. The service industry is the core enterprise of the service industry. Read More

View Article and Full-Text PDF

Recommender system of scholarly papers using public datasets.

AMIA Annu Symp Proc 2021 17;2021:672-679. Epub 2021 May 17.

University of Texas Health Science Center at Houston Houston, TX, USA.

The exponential growth of public datasets in the era of Big Data demands new solutions for making these resources findable and reusable. Therefore, a scholarly recommender system for public datasets is an important tool in the field of information filtering. It will aid scholars in identifying prior and related literature to datasets, saving their time, as well as enhance the datasets reusability. Read More

View Article and Full-Text PDF
September 2021

Research on enterprise knowledge service based on semantic reasoning and data fusion.

Neural Comput Appl 2021 Aug 24:1-16. Epub 2021 Aug 24.

School of Information Management, Jiangxi University of Finance and Economics, Nanchang, 30013 China.

In the era of big data, the field of enterprise risk is facing considerable challenges brought by massive multisource heterogeneous information sources. In view of the proliferation of multisource and heterogeneous enterprise risk information, insufficient knowledge fusion capabilities, and the low level of intelligence in risk management, this article explores the application process of enterprise knowledge service models for rapid responses to risk incidents from the perspective of semantic reasoning and data fusion and clarifies the elements of the knowledge service model in the field of risk management. Based on risk data, risk decision making as the standard, risk events as the driving force, and knowledge graph analysis methods as the power, the risk domain knowledge service process is decomposed into three stages: prewarning, in-event response, and postevent summary. Read More

View Article and Full-Text PDF

Democratizing ownership and participation in the 4th Industrial Revolution: challenges and opportunities in cellular agriculture.

Agric Human Values 2021 Aug 24:1-19. Epub 2021 Aug 24.

Department of Agricultural Economics, Sociology, and Education, Penn State University, Armsby Bldg, University Park, PA 16801 USA.

The emergence of the "4th Industrial Revolution," i.e. the convergence of artificial intelligence, the Internet of Things, advanced materials, and bioengineering technologies, could accelerate socioeconomic insecurities and anxieties or provide beneficial alternatives to the status quo. Read More

View Article and Full-Text PDF

River Basin Cyberinfrastructure in the Big Data Era: An Integrated Observational Data Control System in the Heihe River Basin.

Sensors (Basel) 2021 Aug 11;21(16). Epub 2021 Aug 11.

National Tibetan Plateau Data Center, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China.

River basin cyberinfrastructure with the Internet of Things (IoT) as the core has brought watershed data science into the big data era, greatly improving data acquisition and sharing efficiency. However, challenges in analyzing, processing, and applying very large quantities of observational data remain. Given the observational needs in watershed research, we studied the construction of river basin cyberinfrastructure and developed an integrated observational data control system (IODCS). Read More

View Article and Full-Text PDF

PrepFlow: A Toolkit for Chemical Library Preparation and Management for Virtual Screening.

Mol Inform 2021 Aug 27:e2100139. Epub 2021 Aug 27.

Institut de Chimie de Strasbourg, UMR7177, CNRS, Université de Strasbourg, F-67083, Strasbourg Cedex, France.

In the era of big data in Chemistry, the need for automated tools for virtual screening is compelling. Here, we present PrepFlow a toolkit for chemical library preparation and management. Starting from a list of compounds in SMILES or 2D molecular format, PrepFlow outputs a set of 3D molecular structures ready for use in subsequent drug discovery projects. Read More

View Article and Full-Text PDF

MicroRNA Databases and Tools.

Methods Mol Biol 2022 ;2257:131-166

Department of Computer Science and Bioinformatics and Pattern Recognition Group, Universidade Tecnológica Federal do Paraná (UTFPR), Cornélio Procópio, Brazil.

In this era of big data, sets of methodologies and strategies are designed to extract knowledge from huge volumes of data. However, the cost of where and how to get this information accurately and quickly is extremely important, given the diversity of genomes and the different ways of representing that information. Among the huge set of information and relationships that the genome carries, there are sequences called miRNAs (microRNAs). Read More

View Article and Full-Text PDF
January 2022

A primer on machine learning techniques for genomic applications.

Comput Struct Biotechnol J 2021 31;19:4345-4359. Epub 2021 Jul 31.

Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, Via A. Orabona 4, 70125 Bari, Italy.

High throughput sequencing technologies have enabled the study of complex biological aspects at single nucleotide resolution, opening the big data era. The analysis of large volumes of heterogeneous "omic" data, however, requires novel and efficient computational algorithms based on the paradigm of Artificial Intelligence. In the present review, we introduce and describe the most common machine learning methodologies, and lately deep learning, applied to a variety of genomics tasks, trying to emphasize capabilities, strengths and limitations through a simple and intuitive language. Read More

View Article and Full-Text PDF

Red- and Far-Red-Emitting Zinc Probes with Minimal Phototoxicity for Multiplexed Recording of Orchestrated Insulin Secretion.

Angew Chem Int Ed Engl 2021 Aug 23. Epub 2021 Aug 23.

College of Future Technology, Institute of Molecular Medicine, National Biomedical Imaging Center, Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Peking University, Beijing, 100871, China.

Zinc biology, featuring intertwining signaling networks and critical importance to human health, witnesses exciting opportunities in the big data era of physiology. Here, we report a class of red- and far-red-emitting Zn probes with K values ranging from 190 nM to 74 μM, which are particularly suitable for real-time monitoring the high concentration of Zn co-released with insulin during vesicular secretory events. Compared to the prototypical rhodamine-based Zn probes, the new class exploits morpholino auxochromes which eliminates phototoxicity during long-term live recording of isolated islets. Read More

View Article and Full-Text PDF

Advertising Click-Through Rate Prediction Based on CNN-LSTM Neural Network.

Authors:
Danqing Zhu

Comput Intell Neurosci 2021 13;2021:3484104. Epub 2021 Aug 13.

School of Arts & Communication, Xiamen Institute of Technology, Xiamen 361021, China.

In the era of big data information, how to effectively predict and analyze the click-through rate of information advertising is the key for enterprises in various fields to seek returns. The point rate prediction of advertising is one of the core contents of advertising calculation. The traditional shallow prediction model cannot meet the nonlinear relationship of data processing, and the manual processing of data information extraction method is very resource consuming. Read More

View Article and Full-Text PDF

The Breeding Information Management System (BIMS): an online resource for crop breeding.

Database (Oxford) 2021 08;2021

Department of Horticulture, Washington State University, 45 Johnson Hall, Pullman, WA 99164, USA.

In this era of big data, breeding programs are producing ever larger amounts of data. This necessitates access to efficient management systems to keep track of cross, performance, pedigree, geographical and image-based data, as well as genotyping data. In this article, we report the progress on the Breeding Information Management System (BIMS), a free, secure and online breeding management system that allows breeders to store, manage, archive and analyze their private breeding data. Read More

View Article and Full-Text PDF

Data science in cell imaging.

J Cell Sci 2021 04 1;134(7). Epub 2021 Apr 1.

Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel.

Cell imaging has entered the 'Big Data' era. New technologies in light microscopy and molecular biology have led to an explosion in high-content, dynamic and multidimensional imaging data. Similar to the 'omics' fields two decades ago, our current ability to process, visualize, integrate and mine this new generation of cell imaging data is becoming a critical bottleneck in advancing cell biology. Read More

View Article and Full-Text PDF

Performance comparison between Chaos and quantum-chaos based image encryption techniques.

Multimed Tools Appl 2021 Aug 14:1-43. Epub 2021 Aug 14.

Electronics Engineering Department, J.C.Bose University of Science and Technology YMCA, Faridabad, India.

Today's digital era has undertaken most of the responsibilities of public and private sectors, not only the industries or big organizations dependent on the internet but individual's household needs also lying on it. To make the data transmission/reception confidential and secure for both internet users and internet service providers, a large number of researches have been done in this field. It has proved that cryptography is the best solution for solving this purpose. Read More

View Article and Full-Text PDF

A framework to extract biomedical knowledge from gluten-related tweets: The case of dietary concerns in digital era.

Artif Intell Med 2021 08 25;118:102131. Epub 2021 Jun 25.

CINBIO, Universidade de Vigo, Department of Computer Science, ESEI - Escuela Superior de Ingeniería Informática, 32004 Ourense, Spain; SING Research Group, Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, Spain; CEB, Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal.

Big data importance and potential are becoming more and more relevant nowadays, enhanced by the explosive growth of information volume that is being generated on the Internet in the last years. In this sense, many experts agree that social media networks are one of the internet areas with higher growth in recent years and one of the fields that are expected to have a more significant increment in the coming years. Similarly, social media sites are quickly becoming one of the most popular platforms to discuss health issues and exchange social support with others. Read More

View Article and Full-Text PDF

Fresh Perspectives on an Old Method: Secondary Analysis in a Big Data Era.

Comput Inform Nurs 2021 Aug;39(8):393-399

Author Affiliations: Seattle Children's Hospital (Drs Moore and Thomas), WA; and The University of Arizona College of Nursing (Drs Moore and Gephart), Tucson.

View Article and Full-Text PDF

Electric-Circuit Realization of Fast Quantum Search.

Research (Wash D C) 2021 26;2021:9793071. Epub 2021 Jul 26.

Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurements of Ministry of Education, Beijing Key Laboratory of Nanophotonics & Ultrafine Optoelectronic Systems, School of Physics, Beijing Institute of Technology, Beijing 100081, China.

Quantum search algorithm, which can search an unsorted database quadratically faster than any known classical algorithms, has become one of the most impressive showcases of quantum computation. It has been implemented using various quantum schemes. Here, we demonstrate both theoretically and experimentally that such a fast search algorithm can also be realized using classical electric circuits. Read More

View Article and Full-Text PDF

Functional physiological phenotyping with functional mapping: A general framework to bridge the phenotype-genotype gap in plant physiology.

iScience 2021 Aug 10;24(8):102846. Epub 2021 Jul 10.

College of Life Sciences, China Jiliang University, Hangzhou 310018, China.

The recent years have witnessed the emergence of high-throughput phenotyping techniques. In particular, these techniques can characterize a comprehensive landscape of physiological traits of plants responding to dynamic changes in the environment. These innovations, along with the next-generation genomic technologies, have brought plant science into the big-data era. Read More

View Article and Full-Text PDF

Data for orthopaedic surgeons - A review.

J Clin Orthop Trauma 2021 Oct 15;21:101505. Epub 2021 Jul 15.

Indraprastha Apollo Hospitals, New Delhi, India.

As we step into a technology powered era, where information is available everywhere, managing data forms an important part of professional and everyday life. With developments like online databases, high definition videos and images, social media, robotics, explosion of academic publications, telecommunication, artificial intelligence and internet of things, there is a variable amount of data that the orthopaedic surgeon is exposed to and has to deal with on a regular basis. It is imperative that the surgeon has a basic working knowledge on data and its applications in relation to the field of orthopaedic surgery. Read More

View Article and Full-Text PDF
October 2021

Head and neck surgical oncology training in the current era of molecular oncology.

Authors:
Bipin T Varghese

Oral Oncol 2021 Aug 3:105474. Epub 2021 Aug 3.

Department of Surgical Services, Regional Cancer Centre & Honorary Consultant Head and Neck Surgical Oncologist, Sri Chitra Thirunal Institute for Science and Technology (SCTIMST), Thiruvananthapuram 695011, Kerala, India. Electronic address:

Lack of regional confines limits surgical oncology training, which undoubtedly is an evolving sought-after surgical super speciality programme. Training and practice of region or domain-specific surgical oncology and the recent introduction and popularization of the concept of site-specific multidisciplinary clinics practised worldwide have provided the answer to this issue in a big way. Head and Neck Surgical oncology is one of the classic examples of such developed training pathways globally. Read More

View Article and Full-Text PDF

Metabolomics-Guided Elucidation of Plant Abiotic Stress Responses in the 4IR Era: An Overview.

Metabolites 2021 Jul 8;11(7). Epub 2021 Jul 8.

Department of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg 2006, South Africa.

Plants are constantly challenged by changing environmental conditions that include abiotic stresses. These are limiting their development and productivity and are subsequently threatening our food security, especially when considering the pressure of the increasing global population. Thus, there is an urgent need for the next generation of crops with high productivity and resilience to climate change. Read More

View Article and Full-Text PDF

Prediction of antischistosomal small molecules using machine learning in the era of big data.

Mol Divers 2021 Aug 5. Epub 2021 Aug 5.

Department of Medicine, Loyola University Medical Center, Maywood, IL, 60153, USA.

Schistosomiasis is a neglected tropical disease caused by helminths of the Schistosoma genus. Despite its high morbidity and socio-economic burden, therapeutics are just a handful with praziquantel being the main drug. Praziquantel is an old drug registered for human use in 1982 and has since been administered en masse for chemotherapy, risking the development of resistance, thus the need for new drugs with different mechanisms of action. Read More

View Article and Full-Text PDF