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A multivariate algorithm for identifying contaminated peanut using visible and near-infrared hyperspectral imaging
This study has practical implications for the food industry and future research on deep learning optimization.PMID:37722342 | DOI:10.1016/j.talanta.2023.125187
Source: Talanta - September 18, 2023 Category: Chemistry Authors: Zhen Guo Jing Zhang Jiashuai Sun Haowei Dong Jingcheng Huang Lingjun Geng Shiling Li Xiangzhu Jing Yemin Guo Xia Sun Source Type: research
Application of Multiple Omics to Understand Postoperative Delirium Pathophysiology in Humans
Gerontology. 2023 Sep 18. doi: 10.1159/000533789. Online ahead of print.ABSTRACTDelirium, an acute change in cognition, is common, morbid, and costly, particularly among hospitalized older adults. Despite growing knowledge of its epidemiology, far less is known about delirium pathophysiology. Initial work understanding delirium pathogenesis has focused on assaying single or a limited subset of molecules or genetic loci. Recent technological advances at the forefront of biomarker and drug target discovery have facilitated application of multiple "omics" approaches aimed to provide a more complete understanding of complex di...
Source: Genomics Proteomics ... - September 18, 2023 Category: Genetics & Stem Cells Authors: Sarinnapha M Vasunilashorn Simon T Dillon Edward R Marcantonio Towia A Libermann Source Type: research
An integrated data- and theory-driven crash severity model
Accid Anal Prev. 2023 Sep 16;193:107282. doi: 10.1016/j.aap.2023.107282. Online ahead of print.ABSTRACTFor crash severity modeling, researchers typically view theory-driven models and data-driven models as different or even conflicting approaches. The reason is that the machine-learning models offer good predictability but weak interpretability, while the latter has robust interpretability but moderate predictability. In order to alleviate the tension between them, this study proposes an integrated data- and theory-driven crash-severity model, known as Embedded Fusion model based on Text Vector Representations (TVR-EF), by...
Source: Accident; Analysis and Prevention. - September 18, 2023 Category: Accident Prevention Authors: Dongjie Liu Dawei Li N N Sze Hongliang Ding Yuchen Song Source Type: research
Developing spinal manipulation psychomotor skills competency: A systematic review of teaching methods
CONCLUSION: The use of augmented feedback devices such as human analogue mannequins with force-sensing table technology and computer-connected devices is potentially beneficial in the chiropractic curricula and may facilitate student learning and improvement of spinal manipulation. More studies are required to determine whether psychomotor skill aids translate directly into raised competency levels in novice clinicians.PMID:37721391 | DOI:10.7899/JCE-22-10
Source: The Journal of Chiropractic Education - September 18, 2023 Category: Complementary Medicine Authors: Eleanor de Kock Christopher Yelverton Cornelius Myburgh Source Type: research
Peritoneal Dialysis Patient Training Program to Enhance independence and Prevent Complications: A Scoping Review
CONCLUSION: There are a variety of strategies for dialysis training concerning duration, session length, patient-to-trainer ratio, timing, methods, location, compliance, and the need for retraining. More evidence is needed to assess the impact of PD patient training programs on self-care capabilities and peritonitis incidence. Future studies should investigate the effects of training programs on compliance, self-efficacy, and patient and nurse perspectives.PMID:37720493 | PMC:PMC10505035 | DOI:10.2147/IJNRD.S414447
Source: International Journal of Nephrology and Renovascular Disease - September 18, 2023 Category: Urology & Nephrology Authors: Toni Rahmat Jaelani Kusman Ibrahim Jonny Jonny Sri Hartati Pratiwi Hartiah Haroen Nursiswati Nursiswati Bunga Pinandhita Ramadhani Source Type: research
Dynamic Motion and Human Agents Facilitate Visual Nonadjacent Dependency Learning
Cogn Sci. 2023 Sep;47(9):e13344. doi: 10.1111/cogs.13344.ABSTRACTMany events that humans and other species experience contain regularities in which certain elements within an event predict certain others. While some of these regularities involve tracking the co-occurrences between temporally adjacent stimuli, others involve tracking the co-occurrences between temporally distant stimuli (i.e., nonadjacent dependencies, NADs). Prior research shows robust learning of adjacent dependencies in humans and other species, whereas learning NADs is more difficult, and often requires support from properties of the stimulus to help le...
Source: Cognitive Science - September 18, 2023 Category: Neuroscience Authors: Helen Shiyang Lu Toben H Mintz Source Type: research
Two Computational Approaches to Visual Analogy: Task-Specific Models Versus Domain-General Mapping
Cogn Sci. 2023 Sep;47(9):e13347. doi: 10.1111/cogs.13347.ABSTRACTAdvances in artificial intelligence have raised a basic question about human intelligence: Is human reasoning best emulated by applying task-specific knowledge acquired from a wealth of prior experience, or is it based on the domain-general manipulation and comparison of mental representations? We address this question for the case of visual analogical reasoning. Using realistic images of familiar three-dimensional objects (cars and their parts), we systematically manipulated viewpoints, part relations, and entity properties in visual analogy problems. We com...
Source: Cognitive Science - September 18, 2023 Category: Neuroscience Authors: Nicholas Ichien Qing Liu Shuhao Fu Keith J Holyoak Alan L Yuille Hongjing Lu Source Type: research
The effectiveness of self: A meta-analysis of using self-referential encoding techniques in education
CONCLUSIONS: Our results suggest that incorporating self-referential encoding techniques on negative materials shows an aversive effect. Overall, there is a universal benefit to using self-referential encoding techniques as an appropriate design guideline in educational contexts. Implications for teaching practice and future directions are discussed. Further studies are needed to investigate the effectiveness in more diverse educational and teaching situations.PMID:37722845 | DOI:10.1111/bjep.12636
Source: The British Journal of Educational Psychology - September 18, 2023 Category: Psychiatry & Psychology Authors: Zheng Liu Jiahui Wen Yikang Liu Chuan-Peng Hu Source Type: research
Machine learning developed a programmed cell death signature for predicting prognosis and immunotherapy benefits in lung adenocarcinoma
CONCLUSION: Our study developed a novel CDS for LUAD. The CDS served as an indicator for predicting the prognosis and immunotherapy benefits of LAUD patients.PMID:37722290 | DOI:10.1016/j.tranon.2023.101784
Source: Translational Oncology - September 18, 2023 Category: Cancer & Oncology Authors: Dongxiao Ding Liangbin Wang Yunqiang Zhang Ke Shi Yaxing Shen Source Type: research
Modelling enzyme inhibition toxicity of ionic liquid from molecular structure via convolutional neural network model
SAR QSAR Environ Res. 2023 Sep 18:1-15. doi: 10.1080/1062936X.2023.2255517. Online ahead of print.ABSTRACTDeep learning (DL) methods further promote the development of quantitative structure-activity/property relationship (QSAR/QSPR) models by dealing with complex relationships between data. An acetylcholinesterase inhibitory toxicity model of ionic liquids (ILs) was established using a convolution neural network (CNN) combined with support vector machine (SVM), random forest (RF) and multilayer perceptron (MLP). A CNN model was proposed for feature self-learning and extraction of ILs. By comparing with the model results t...
Source: SAR and QSAR in Environmental Research - September 18, 2023 Category: Environmental Health Authors: R Zhang Y Chen D Fan T Liu Z Ma Y Dai Y Wang Z Zhu Source Type: research
Mark his motives: A motivational attribution perspective on observer responses to peer helping behaviors
CONCLUSION: The results suggest that prosocial motivational attributions and impression management motivational attributions are key factors in determining whether observers have approach- or avoidance-oriented emotions and behaviors toward coworker helping. Accordingly, individual employees and managers should focus on employees' motivation to help others in order to promote mutual support and harmony in the workplace.PMID:37718830 | DOI:10.3233/WOR-220647
Source: Work - September 18, 2023 Category: Occupational Health Authors: Di Zhu Xiaoming Tian Rui Li Source Type: research
Graph Neural Network Interatomic Potential Ensembles with Calibrated Aleatoric and Epistemic Uncertainty on Energy and Forces
Phys. Chem. Chem. Phys., 2023, Accepted Manuscript DOI: 10.1039/D3CP02143B, PaperJonas Busk, Mikkel Schmidt, Ole Winther, Tejs Vegge, Peter Bj ørn Jørgensen Inexpensive machine learning potentials are increasingly being used to speed up structural optimization and molecular dynamics simulations of materials by iteratively predicting and applying interatomic forces. In these settings, it... The content of this RSS Feed (c) The Royal Society of Chemistry
Source: RSC - Phys. Chem. Chem. Phys. latest articles - September 18, 2023 Category: Chemistry Authors: Jonas Busk Source Type: research
Application of machine learning and artificial intelligence in the diagnosis and classification of polycystic ovarian syndrome: a systematic review
ConclusionArtificial intelligence and machine learning provide a high diagnostic and classification performance in detecting PCOS, thereby providing an avenue for early diagnosis of this disorder. However, AI-based studies should use standardized PCOS diagnostic criteria to enhance the clinical applicability of AI/ML in PCOS and improve adherence to methodological and reporting guidelines for maximum diagnostic utility.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42022295287.
Source: Frontiers in Endocrinology - September 18, 2023 Category: Endocrinology Source Type: research
Medical education empowered by generative artificial intelligence large language models
Trends Mol Med. 2023 Sep 15:S1471-4914(23)00211-3. doi: 10.1016/j.molmed.2023.08.012. Online ahead of print.ABSTRACTGenerative artificial intelligence (GAI) large language models (LLMs), like ChatGPT, have become the world's fastest growing applications. Here, we provide useful strategies for educators in medical and health science (M&HS) to integrate GAI-LLMs into learning and teaching practice, ultimately enhancing students' digital capability.PMID:37718142 | DOI:10.1016/j.molmed.2023.08.012
Source: Molecular Medicine - September 17, 2023 Category: Molecular Biology Authors: Tanisha Jowsey Jessica Stokes-Parish Rachelle Singleton Michael Todorovic Source Type: research
A new paradigm in lignocellulolytic enzyme cocktail optimization: Free from expert-level prior knowledge and experimental datasets
Bioresour Technol. 2023 Sep 15:129758. doi: 10.1016/j.biortech.2023.129758. Online ahead of print.ABSTRACTEffectively pairing diverse lignocellulolytic enzyme cocktails with intricately structured lignocellulosic substrates is an enduring challenge for science and technology. To date, extensive trial-and-error remains the primary approach and no deep-learning methods were developed to address it due to limited experimental data and incomplete expert-level knowledge of enzyme-cocktail-substrate structure-dynamics-function relationships. Here, a novel model is developed to tackle this issue in efficient, cost-effective, and ...
Source: Bioresource Technology - September 17, 2023 Category: Biotechnology Authors: Le Gao Zhuohang Yu Shengjie Wang Yuejie Hou Shouchang Zhang Chichun Zhou Xin Wu Source Type: research
