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Broadband sensory networks with locally stored responsivities for neuromorphic machine vision
Sci Adv. 2023 Sep 15;9(37):eadi5104. doi: 10.1126/sciadv.adi5104. Epub 2023 Sep 15.ABSTRACTAs the most promising candidates for the implementation of in-sensor computing, retinomorphic vision sensors can constitute built-in neural networks and directly implement multiply-and-accumulation operations using responsivities as the weights. However, existing retinomorphic vision sensors mainly use a sustained gate bias to maintain the responsivity due to its volatile nature. Here, we propose an ion-induced localized-field strategy to develop retinomorphic vision sensors with nonvolatile tunable responsivity in both positive and ...
Source: Adv Data - September 15, 2023 Category: Epidemiology Authors: Guo-Xin Zhang Zhi-Cheng Zhang Xu-Dong Chen Lixing Kang Yuan Li Fu-Dong Wang Lei Shi Ke Shi Zhi-Bo Liu Jian-Guo Tian Tong-Bu Lu Jin Zhang Source Type: research
Time series prediction of the chemical components of PM < sub > 2.5 < /sub > based on a deep learning model
This study provides insight into improving the accuracy of modeling-based detection methods and promotes the development of integrated air pollution monitoring toward a more sustainable direction.PMID:37714468 | DOI:10.1016/j.chemosphere.2023.140153
Source: Chemosphere - September 15, 2023 Category: Chemistry Authors: Kai Liu Yuanhang Zhang Huan He Hui Xiao Siyuan Wang Yuteng Zhang Huiming Li Xin Qian Source Type: research
TransQA: deep hybrid transformer network for measurement-guided volumetric dose prediction of pre-treatment patient-specific quality assurance
Phys Med Biol. 2023 Sep 15. doi: 10.1088/1361-6560/acfa5e. Online ahead of print.ABSTRACTOBJECTIVE: Performing pre-treatment patient-specific quality assurance (prePSQA) is considered an essential, time-consuming, and resource-intensive task for volumetric modulated arc radiotherapy (VMAT) which confirms the dose accuracy and ensure patient safety. Most current machine learning and deep learning approaches stack excessive convolutional/pooling operations (CPs) to predict prePSQA with two-dimensional or one-dimensional information input. However, these models generally present limitations in explicitly modeling long-range d...
Source: Physics in Medicine and Biology - September 15, 2023 Category: Physics Authors: Lingpeng Zeng Minghui Zhang Yun Zhang Zhongsheng Zou Yu Guan Bin Huang Xiuwen Yu Shenggou Ding Qiegen Liu Changfei Gong Source Type: research
Analysis and prediction of liver volume change maps derived from computational tomography scans acquired pre- and post-radiation therapy
This study leverages the use of deep learning-based segmentation and biomechanical deformable image registration (DIR) to analyze and predict this relationship. Pre- and Post-EBRT imaging data were collected for 100 patients treated for HCC, CC or CRC with IMRT with prescription doses ranging from 50 to 100 Gy delivered in 10 to 28 fractions. For each patient, DIR between the portal and venous (PV) phase of a diagnostic CT scan acquired before RT planning, and a PV phase of a diagnostic CT scan acquired after the end of RT (on average 147±36 days) was performed to calculate Jacobian maps representing volume changes in the...
Source: Physics in Medicine and Biology - September 15, 2023 Category: Physics Authors: Guillaume Cazoulat Aashish C Gupta Mais M Al Taie Eugene J Koay Kristy K Brock Source Type: research
Ring artifacts correction for computed tomography image using unsupervised contrastive learning
Phys Med Biol. 2023 Sep 15. doi: 10.1088/1361-6560/acfa60. Online ahead of print.ABSTRACTComputed tomography (CT) is a widely employed imaging technology for disease detection. However, CT images often suffer from ring artifacts, which may result from hardware defects and other factors. These artifacts compromise image quality and impede diagnosis. To address this challenge, we propose a novel method based on dual contrast learning image style transformation network model (DCLGAN) that effectively eliminates ring artifacts from CT images while preserving texture details. 
Approach: Our method involves simulating ri...
Source: Physics in Medicine and Biology - September 15, 2023 Category: Physics Authors: Tangsheng Wang Xuan Liu Chulong Zhang Yutong He Yinping Chan Yaoqin Xie Xiaokun Liang Source Type: research
Functional outcome prediction after spinal cord injury using ensemble machine learning
CONCLUSIONS: Our study revealed that functional prognostication could be achieved using machine-learning methods with features present at the time of rehabilitation admission. Goals can be set at the beginning of rehabilitation. Moreover, our model can be utilized to evaluate advanced medical treatments, such as regenerative medicine.PMID:37714506 | DOI:10.1016/j.apmr.2023.08.011
Source: Health Physics - September 15, 2023 Category: Physics Authors: Chihiro Kato Osamu Uemura Yasunori Sato Tetsuya Tsuji Source Type: research
Readiness of Pharmacists as Providers of Social Determinants of Health and Call to Action
Am J Pharm Educ. 2023 Sep;87(9):100051. doi: 10.1016/j.ajpe.2022.10.011. Epub 2023 Mar 15.ABSTRACTSocial determinants of health (SDOH) are defined as the conditions in the environments where people are born, live, learn, work, play, worship, and age. SDOH has an enormous impact on achieving the goals set by Healthy People 2030. With their education and training, pharmacists are in an ideal position to provide SDOH services. Community pharmacists should take innovative approaches in collaboration with the Community Pharmacy Enhanced Services Network to develop standard protocols for SDOH and reimbursements for these service...
Source: American Journal of Pharmaceutical Education - September 15, 2023 Category: Universities & Medical Training Authors: M Omar Faruk Khan L Douglas Ried Source Type: research
Backward Design to Combat Curricular Expansion in a Large, Interdisciplinary, Team-Taught Course
CONCLUSION: Using backward design as a framework to intentionally evaluate didactic content volume and assessment alignment can address curricular expansion while maintaining student learning and decreasing student and instructor stress.PMID:37714652 | DOI:10.1016/j.ajpe.2022.12.009
Source: American Journal of Pharmaceutical Education - September 15, 2023 Category: Universities & Medical Training Authors: Kristine M Cline Marjorie M Winhoven Victoria L Williams Katherine A Kelley Brianne L Porter Source Type: research
Estimating the geographical patterns and health risks associated with PM < sub > 2.5 < /sub > -bound heavy metals to guide PM < sub > 2.5 < /sub > control targets in China based on machine-learning algorithms
In this study, we compiled a substantial dataset consisting of the concentrations of eight PBHMs, including As, Cd, Cr, Cu, Mn, Ni, Pb and Zn, across different cities in China. To improve prediction accuracy, we enhanced the traditional land-use regression (LUR) model by incorporating emission source-related variables and employing the best-fitted machine-learning algorithm, which was applied to predict PBHM concentrations, analyze geographical patterns and assess the health risks associated with metals under different PM2.5 control targets. Our model exhibited excellent performance in predicting the concentrations of PBHM...
Source: Environmental Pollution - September 15, 2023 Category: Environmental Health Authors: Tong Lyu Yilin Tang Hongbin Cao Yue Gao Xu Zhou Wei Zhang Ruidi Zhang Yanxue Jiang Source Type: research
Congener-specific uptake and accumulation of bisphenols in edible plants: Binding to prediction of bioaccumulation by attention mechanism multi-layer perceptron machine learning model
In this study, the uptake, translocation, and accumulation of five bisphenols (BPs) in carrot and lettuce plants were investigated through hydroponic culture (duration of 168 h) and soil culture (duration of 42 days) systems. The results suggested a higher bioconcentration factor (BCF) of bisphenol AF (BPAF) in plants than that of the other four BPs. A positive correlation was found between the log BCF and the log Kow of BPs (R2carrot = 0.991, R2lettuce = 0.784, P < 0.05), while the log (translocation factor) exhibited a negative correlation with the log Kow (R2carrot = 0.882, R2lettuce = 0.723, P < 0.05). The result...
Source: Environmental Pollution - September 15, 2023 Category: Environmental Health Authors: Xindong Yang Qinghua Zhou Qianwen Wang Juan Wu Haofeng Zhu Anping Zhang Jianqiang Sun Source Type: research
Physical model-based cascaded generative adversarial networks for accelerating quantitative multi-parametric magnetic resonance imaging
CONCLUSION: Compared with other existing methods, the physical model-based cascaded generative adversarial networks can reconstruct more image details and features, thus improving the quality and accuracy of the reconstructed images.PMID:37712278 | DOI:10.12122/j.issn.1673-4254.2023.08.18
Source: Journal of Southern Medical University - September 15, 2023 Category: Universities & Medical Training Authors: Y Liu Z Chu Y Zhang Source Type: research
Time series prediction of the chemical components of PM < sub > 2.5 < /sub > based on a deep learning model
This study provides insight into improving the accuracy of modeling-based detection methods and promotes the development of integrated air pollution monitoring toward a more sustainable direction.PMID:37714468 | DOI:10.1016/j.chemosphere.2023.140153
Source: Chemosphere - September 15, 2023 Category: Chemistry Authors: Kai Liu Yuanhang Zhang Huan He Hui Xiao Siyuan Wang Yuteng Zhang Huiming Li Xin Qian Source Type: research
A Dual-Aware deep learning framework for identification of glioma isocitrate dehydrogenase genotype using magnetic resonance amide proton transfer modalities
CONCLUSION: The proposed deep learning algorithm model constructed based on the image characteristics of the APT modality is effective for glioma IDH genotyping and identification task and may potentially replace the commonly used T1CE modality to avoid contrast agent injection and achieve non- invasive IDH genotyping.PMID:37712275 | DOI:10.12122/j.issn.1673-4254.2023.08.15
Source: Journal of Southern Medical University - September 15, 2023 Category: Universities & Medical Training Authors: Z Chu Y Qu T Zhong S Liang Z Wen Y Zhang Source Type: research
Protein classification by autofluorescence spectral shape analysis using machine learning
Talanta. 2023 Sep 9;267:125167. doi: 10.1016/j.talanta.2023.125167. Online ahead of print.ABSTRACTDepending on the relative numbers and spatial arrangement of Tryptophan (Trp; W) and Tyrosine (Tyr; Y) residues, different proteins produce distinct autofluorescence (AF) spectral shapes when excited at ∼280 nm. Yet, considering the vast number and heterogeneous forms in nature, visual analysis and precise identification of proteins based on their AF spectra is challenging and further compounded in cases when different proteins produce substantially similar AF spectral shapes. There is, thus, a serious need to develop a meth...
Source: Talanta - September 15, 2023 Category: Chemistry Authors: Darshan Chikkanayakanahalli Mukunda Jackson Rodrigues Subhash Chandra Nirmal Mazumder Alex Vitkin Krishna Kishore Mahato Source Type: research
Association between co-exposure to phenols, phthalates, and polycyclic aromatic hydrocarbons with the risk of frailty
Environ Sci Pollut Res Int. 2023 Sep 15. doi: 10.1007/s11356-023-29887-7. Online ahead of print.ABSTRACTThe phenomenon of population aging has brought forth the challenge of frailty. Nevertheless, the contribution of environmental exposure to frailty remains ambiguous. Our objective was to investigate the association between phenols, phthalates (PAEs), and polycyclic aromatic hydrocarbons (PAHs) with frailty. We constructed a 48-item frailty index using data from the National Health and Nutrition Examination Survey (NHANES). The exposure levels of 20 organic contaminants were obtained from the survey circle between 2005 an...
Source: Environmental Science and Pollution Research International - September 15, 2023 Category: Environmental Health Authors: Wenxiang Li Guangyi Huang Ningning Tang Peng Lu Li Jiang Jian Lv Yuanjun Qin Yunru Lin Fan Xu Daizai Lei Source Type: research
