keyword
https://read.qxmd.com/read/38436579/an-intelligent-early-warning-system-for-harmful-algal-blooms-harnessing-the-power-of-big-data-and-deep-learning
#1
JOURNAL ARTICLE
Jing Qian, Li Qian, Nan Pu, Yonghong Bi, Andre Wilhelms, Stefan Norra
Harmful algal blooms (HABs) pose a significant ecological threat and economic detriment to freshwater environments. In order to develop an intelligent early warning system for HABs, big data and deep learning models were harnessed in this study. Data collection was achieved utilizing the vertical aquatic monitoring system (VAMS). Subsequently, the analysis and stratification of the vertical aquatic layer were conducted employing the "DeepDPM-Spectral Clustering" method. This approach drastically reduced the number of predictive models and enhanced the adaptability of the system...
March 4, 2024: Environmental Science & Technology
https://read.qxmd.com/read/38422802/the-association-of-hospital-profitability-and-digital-maturity-an-explorative-study-using-data-from-the-german-digitalradar-project
#2
JOURNAL ARTICLE
Justus Vogel, Johannes Hollenbach, Alexander Haering, Boris Augurzky, Alexander Geissler
INTRODUCTION: German hospitals largely rely on public investments for digitization. As these have been insufficient, hospitals had to use own profits to foster digital transformation. Thus, we assess if profitability affects digital maturity, and what other factors might be influential. METHODS: We use digital maturity data from the DigitalRadar (DR) project (2021) and financial statement data from the Hospital Rating Report from 2017 to 2019 (n = 860). We run linear regressions with the DR-score (continuous variable from 0 to 100) as dependent and three-year average EBITDA margin as independent variable...
February 11, 2024: Health Policy
https://read.qxmd.com/read/38397680/consore-a-powerful-federated-data-mining-tool-driving-a-french-research-network-to-accelerate-cancer-research
#3
JOURNAL ARTICLE
Julien Guérin, Amine Nahid, Louis Tassy, Marc Deloger, François Bocquet, Simon Thézenas, Emmanuel Desandes, Marie-Cécile Le Deley, Xavier Durando, Anne Jaffré, Ikram Es-Saad, Hugo Crochet, Marie Le Morvan, François Lion, Judith Raimbourg, Oussama Khay, Franck Craynest, Alexia Giro, Yec'han Laizet, Aurélie Bertaut, Frederik Joly, Alain Livartowski, Pierre Heudel
BACKGROUND: Real-world data (RWD) related to the health status and care of cancer patients reflect the ongoing medical practice, and their analysis yields essential real-world evidence. Advanced information technologies are vital for their collection, qualification, and reuse in research projects. METHODS: UNICANCER, the French federation of comprehensive cancer centres, has innovated a unique research network: Consore. This potent federated tool enables the analysis of data from millions of cancer patients across eleven French hospitals...
February 7, 2024: International Journal of Environmental Research and Public Health
https://read.qxmd.com/read/38339656/pufchain-3-0-hardware-assisted-distributed-ledger-for-robust-authentication-in-healthcare-cyber-physical-systems
#4
JOURNAL ARTICLE
Venkata K V V Bathalapalli, Saraju P Mohanty, Elias Kougianos, Vasanth Iyer, Bibhudutta Rout
This article presents a novel hardware-assisted distributed ledger-based solution for simultaneous device and data security in smart healthcare. This article presents a novel architecture that integrates PUF, blockchain, and Tangle for Security-by-Design (SbD) of healthcare cyber-physical systems (H-CPSs). Healthcare systems around the world have undergone massive technological transformation and have seen growing adoption with the advancement of Internet-of-Medical Things (IoMT). The technological transformation of healthcare systems to telemedicine, e-health, connected health, and remote health is being made possible with the sophisticated integration of IoMT with machine learning, big data, artificial intelligence (AI), and other technologies...
January 31, 2024: Sensors
https://read.qxmd.com/read/38306788/research-and-application-of-deep-learning-based-sleep-staging-data-modeling-validation-and-clinical-practice
#5
REVIEW
Huijun Yue, Zhuqi Chen, Wenbin Guo, Lin Sun, Yidan Dai, Yiming Wang, Wenjun Ma, Xiaomao Fan, Weiping Wen, Wenbin Lei
Over the past few decades, researchers have attempted to simplify and accelerate the process of sleep stage classification through various approaches; however, only a few such approaches have gained widespread acceptance. Artificial intelligence technology, particularly deep learning, is promising for earning the trust of the sleep medicine community in automated sleep-staging systems, thus facilitating its application in clinical practice and integration into daily life. We aimed to comprehensively review the latest methods that are applying deep learning for enhancing sleep staging efficiency and accuracy...
January 11, 2024: Sleep Medicine Reviews
https://read.qxmd.com/read/38303438/toward-the-internet-of-medical-things-architecture-trends-and-challenges
#6
JOURNAL ARTICLE
Qinwang Niu, Haoyue Li, Yu Liu, Zhibo Qin, Li-Bo Zhang, Junxin Chen, Zhihan Lyu
In recent years, the growing pervasiveness of wearable technology has created new opportunities for medical and emergency rescue operations to protect users' health and safety, such as cost-effective medical solutions, more convenient healthcare and quick hospital treatments, which make it easier for the Internet of Medical Things (IoMT) to evolve. The study first presents an overview of the IoMT before introducing the IoMT architecture. Later, it portrays an overview of the core technologies of the IoMT, including cloud computing, big data and artificial intelligence, and it elucidates their utilization within the healthcare system...
January 2024: Mathematical Biosciences and Engineering: MBE
https://read.qxmd.com/read/38302604/brain-tumor-detection-from-images-and-comparison-with-transfer-learning-methods-and-3-layer-cnn
#7
JOURNAL ARTICLE
Mohammad Zafer Khaliki, Muhammet Sinan Başarslan
Health is very important for human life. In particular, the health of the brain, which is the executive of the vital resource, is very important. Diagnosis for human health is provided by magnetic resonance imaging (MRI) devices, which help health decision makers in critical organs such as brain health. Images from these devices are a source of big data for artificial intelligence. This big data enables high performance in image processing classification problems, which is a subfield of artificial intelligence...
February 1, 2024: Scientific Reports
https://read.qxmd.com/read/38147857/clinical-research-informatics-contributions-from-2022
#8
JOURNAL ARTICLE
Xavier Tannier, Dipak Kalra
OBJECTIVES: To summarize key contributions to current research in the field of Clinical Research Informatics (CRI) and to select best papers published in 2022. METHOD: A bibliographic search using a combination of Medical Subject Headings (MeSH) descriptors and free-text terms on CRI was performed using PubMed, followed by a double-blind review in order to select a list of candidate best papers to be then peer-reviewed by external reviewers. After peer-review ranking, a consensus meeting between the two section editors and the editorial team was organized to finally conclude on the selected three best papers...
August 2023: Yearbook of Medical Informatics
https://read.qxmd.com/read/38145679/deep-learning-based-efficient-drone-borne-sensing-of-cyanobacterial-blooms-using-a-clique-based-feature-extraction-approach
#9
JOURNAL ARTICLE
Jihoon Shin, Gunhyeong Lee, TaeHo Kim, Kyung Hwa Cho, Seok Min Hong, Do Hyuck Kwon, JongCheol Pyo, YoonKyung Cha
Recent advances in remote sensing techniques provide a new horizon for monitoring the spatiotemporal variations of harmful algal blooms (HABs) using hyperspectral data in inland water. In this study, a hierarchical concatenated variational autoencoder (HCVAE) is proposed as an efficient and accurate deep learning (DL) based bio-optical model. To demonstrate its usefulness in retrieving algal pigments, the HCVAE is applied to bloom-prone regions in Daecheong Lake, South Korea. By abstracting the similarity between highly related features using layer-wise clique-based latent-feature extraction, HCVAE reduces the computational loads in deriving outputs while preventing performance degradation...
December 23, 2023: Science of the Total Environment
https://read.qxmd.com/read/38110422/elderly-and-visually-impaired-indoor-activity-monitoring-based-on-wi-fi-and-deep-hybrid-convolutional-neural-network
#10
JOURNAL ARTICLE
K Deepa, Nebojsa Bacanin, S S Askar, Mohamed Abouhawwash
A drop in physical activity and a deterioration in the capacity to undertake daily life activities are both connected with ageing and have negative effects on physical and mental health. An Elderly and Visually Impaired Human Activity Monitoring (EV-HAM) system that keeps tabs on a person's routine and steps in if a change in behaviour or a crisis might greatly help an elderly person or a visually impaired. These individuals may find greater freedom with the help of an EVHAM system. As the backbone of human-centric applications like actively supported living and in-home monitoring for the elderly and visually impaired, an EVHAM system is essential...
December 18, 2023: Scientific Reports
https://read.qxmd.com/read/38083735/lethe-a-digital-intervention-for-cognitive-decline
#11
JOURNAL ARTICLE
Vasileios S Loukas, Thomas Kassiotis, Ignacio Lamata Martinez, Lefteris Koumakis, Jeroen Bruinsma, Roberto Pasciuti, Monica Balatresi, Ville Tenhunen, Adam Fiakkas, Lelia Ataliani, Georgia S Karanasiou, Manolis Tsiknakis, Hannes Hilberger, Markus Bodenler, Bianca Schnalzer, Simone Huber, Mattia Pirani, Matteo Colombo, Sten Hanke, Dimitrios I Fotiadis
Dementia is the main cause of disability in elderly populations. It has been shown that the risk factors of dementia are a mixture of pathological, lifestyle and heritable factors, with some of those being provably modifiable. Early diagnosis of dementia and approaches to slow down its evolution are currently the most prominent management methodologies due to lack of a cure. For that reason, a plethora of home-based assistive technologies for dementia management do exist, with most of them focusing on the improvement of memory and thinking...
July 2023: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://read.qxmd.com/read/38047232/quantitative-assessment-of-mitochondrial-morphology-relevant-for-studies-on-cellular-health-and-environmental-toxicity
#12
JOURNAL ARTICLE
Sophie Charrasse, Titouan Poquillon, Charlotte Saint-Omer, Manuela Pastore, Benoit Bordignon, Richard E Frye, Christelle Reynes, Victor Racine, Abdel Aouacheria
Mitochondria are essential organelles that play crucial roles in cellular energy metabolism, calcium signaling and apoptosis. Their importance in tissue homeostasis and stress responses, combined to their ability to transition between various structural and functional states, make them excellent organelles for monitoring cellular health. Quantitative assessment of mitochondrial morphology can therefore provide valuable insights into environmentally-induced cell damage. High-content screening (HCS) provides a powerful tool for analyzing organelles and cellular substructures...
2023: Computational and Structural Biotechnology Journal
https://read.qxmd.com/read/37999807/a-lightweight-deep-learning-framework-for-automatic-mri-data-sorting-and-artifacts-detection
#13
JOURNAL ARTICLE
Ronghui Gao, Guoting Luo, Renxin Ding, Bo Yang, Huaiqiang Sun
The purpose of this study is to develop a lightweight and easily deployable deep learning system for fully automated content-based brain MRI sorting and artifacts detection. 22092 MRI volumes from 4076 patients between 2017 and 2021 were involved in this retrospective study. The dataset mainly contains 4 common contrast (T1-weighted (T1w), contrast-enhanced T1-weighted (T1c), T2-weighted (T2w), fluid-attenuated inversion recovery (FLAIR)) in three perspectives (axial, coronal, and sagittal), and magnetic resonance angiography (MRA), as well as three typical artifacts (motion, aliasing, and metal artifacts)...
November 24, 2023: Journal of Medical Systems
https://read.qxmd.com/read/37583833/heart-rate-estimation-from-ballistocardiogram-signals-processing-via-low-cost-telemedicine-architectures-a-comparative-performance-evaluation
#14
JOURNAL ARTICLE
Adriano Tramontano, Oscar Tamburis, Salvatore Cioce, Salvatore Venticinque, Mario Magliulo
Medical devices (MDs) have been designed for monitoring the parameters of patients in many sectors. Nonetheless, despite being high-performing and reliable, they often turn out to be expensive and intrusive. In addition, MDs are almost exclusively used in controlled, hospital-based environments. Paving a path of technological innovation in the clinical field, a very active line of research is currently dealing with the possibility to rely on non-medical-graded low-cost devices, to develop unattended telemedicine (TM) solutions aimed at non-invasively gathering data, signals, and images...
2023: Frontiers in digital health
https://read.qxmd.com/read/37451448/large-scale-seasonal-forecasts-of-river-discharge-by-coupling-local-and-global-datasets-with-a-stacked-neural-network-case-for-the-loire-river-system
#15
JOURNAL ARTICLE
M T Vu, A Jardani, M Krimissa, F Zaoui, N Massei
Accurate prediction of river discharge is critical for a wide range of sectors, from human activities to environmental hazard management, especially in the face of increasing demand for water resources and climate change. To address this need, a multivariate model that incorporates both local and global data sources, including river and piezometer gauges, sea level, and climate parameters. By employing phase shift analysis, the model optimizes correlations between the target discharge and 12 parameters related to hydrologic and climatic systems, all sampled daily...
July 12, 2023: Science of the Total Environment
https://read.qxmd.com/read/37448836/successes-and-challenges-of-artificial-intelligence-in-cardiology
#16
REVIEW
Bert Vandenberk, Derek S Chew, Dinesh Prasana, Sunny Gupta, Derek V Exner
In the past decades there has been a substantial evolution in data management and data processing techniques. New data architectures made analysis of big data feasible, healthcare is orienting towards personalized medicine with digital health initiatives, and artificial intelligence (AI) is becoming of increasing importance. Despite being a trendy research topic, only very few applications reach the stage where they are implemented in clinical practice. This review provides an overview of current methodologies and identifies clinical and organizational challenges for AI in healthcare...
2023: Frontiers in digital health
https://read.qxmd.com/read/37420917/smart-chemical-sensor-and-biosensor-networks-for-healthcare-4-0
#17
JOURNAL ARTICLE
Lawrence He, Mark Eastburn, James Smirk, Hong Zhao
Driven by technological advances from Industry 4.0, Healthcare 4.0 synthesizes medical sensors, artificial intelligence (AI), big data, the Internet of things (IoT), machine learning, and augmented reality (AR) to transform the healthcare sector. Healthcare 4.0 creates a smart health network by connecting patients, medical devices, hospitals, clinics, medical suppliers, and other healthcare-related components. Body chemical sensor and biosensor networks (BSNs) provide the necessary platform for Healthcare 4...
June 20, 2023: Sensors
https://read.qxmd.com/read/37409078/a-computer-architecture-based-on-disruptive-information-technologies-for-drug-management-in-hospitals
#18
JOURNAL ARTICLE
Ricardo Chalmeta, Andres Navarro-Ruiz, Leticia Soriano-Irigaray
The drug management currently carried out in hospitals is inadequate due to several factors, such as processes carried out manually, the lack of visibility of the hospital supply chain, the lack of standardized identification of medicines, inefficient stock management, an inability to follow the traceability of medicines, and poor data exploitation. Disruptive information technologies could be used to develop and implement a drug management system in hospitals that is innovative in all its phases and allows these problems to be overcome...
2023: PeerJ. Computer Science
https://read.qxmd.com/read/37364796/application-of-image-super-resolution-recognition-and-artificial-intelligence-system-in-repairing-students-psychological-education-problems
#19
JOURNAL ARTICLE
Shulian Li, Haibin Jiang, Zhiqiang Ding, Shilong Fan, Nan Li, Xv Li
With the continuous development of society, people's life pressure is constantly increasing, and the mental health problems of college students are becoming increasingly prominent, bringing many challenges to their education and management. Universities should not only cultivate students' theoretical and professional knowledge and practical skills, but also attach importance to their mental health and effectively implement psychological education. Therefore, it is very necessary to develop and design a simple and effective student psychological evaluation system...
June 24, 2023: Preventive Medicine
https://read.qxmd.com/read/37360143/survey-on-sensors-and-smart-devices-for-iot-enabled-intelligent-healthcare-system
#20
REVIEW
Swati Sandeep Chopade, Hari Prabhat Gupta, Tanima Dutta
The Internet of Things (IoT) in the healthcare system is rapidly changing from the conventional hospital and concentrated specialist behavior to a distributed, patient-centric approach. With the advancement of new techniques, a patient needs sophisticated healthcare requirements. IoT-enabled intelligent health monitoring system with sensors and devices is a patient analysis technique to monitor the patient 24 h a day. IoT is swapping the architecture and has improved the application of different complex systems...
June 12, 2023: Wireless Personal Communications
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