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JOURNAL ARTICLE
Maryam Motamedi, Jessica Dawson, Na Li, Douglas G Down, Nancy M Heddle
Platelet products are both expensive and have very short shelf lives. As usage rates for platelets are highly variable, the effective management of platelet demand and supply is very important yet challenging. The primary goal of this paper is to present an efficient forecasting model for platelet demand at Canadian Blood Services (CBS). To accomplish this goal, five different demand forecasting methods, ARIMA (Auto Regressive Integrated Moving Average), Prophet, lasso regression (least absolute shrinkage and selection operator), random forest, and LSTM (Long Short-Term Memory) networks are utilized and evaluated via a rolling window method...
2024: PloS One
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JOURNAL ARTICLE
Dong Ouyang, Yong Liang, Jinfeng Wang, Le Li, Ning Ai, Junning Feng, Shanghui Lu, Shuilin Liao, Xiaoying Liu, Shengli Xie
Existing studies have shown that the abnormal expression of microRNAs (miRNAs) usually leads to the occurrence and development of human diseases. Identifying disease-related miRNAs contributes to studying the pathogenesis of diseases at the molecular level. As traditional biological experiments are time-consuming and expensive, computational methods have been used as an effective complement to infer the potential associations between miRNAs and diseases. However, most of the existing computational methods still face three main challenges: (i) learning of high-order relations; (ii) insufficient representation learning ability; (iii) importance learning and integration of multi-view embedding representation...
April 2024: PLoS Computational Biology
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JOURNAL ARTICLE
C P Ranjith, Mayakannan Krishnan, Vysakh Raveendran, Lalit Chaudhari, Siddhartha Laskar
Utilising Machine Learning (ML) models to predict dosimetric parameters in pencil beam scanning proton therapy presents a promising and practical approach. The study developed Artificial Neural Network (ANN) models to predict proton beam spot size and relative positional errors using 9000 proton spot data. The irradiation log files as input variables and corresponding scintillation detector measurements as the label values. The ANN models were developed to predict six variables: spot size in the x -axis, y -axis, major axis, minor axis, and relative positional errors in the x -axis and y -axis...
April 22, 2024: Biomedical Physics & Engineering Express
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JOURNAL ARTICLE
Sai Zhang, Yunjie Wu, Xiaowang Zhang, Zhiyong Feng, Liang Wan, Zhiqiang Zhuang
Textbook question answering (TQA) task aims to infer answers for given questions from a multimodal context, including text and diagrams. The existing studies have aggregated intramodal semantics extracted from a single modality but have yet to capture the intermodal semantics between different modalities. A major challenge in learning intermodal semantics is maintaining lossless intramodal semantics while bridging the gap of semantics caused by heterogeneity. In this article, we propose an intermodal relation-aware heterogeneous graph network (IMR-HGN) to extract the intermodal semantics for TQA, which aggregates different modalities while learning features rather than representing them independently...
April 23, 2024: IEEE Transactions on Neural Networks and Learning Systems
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JOURNAL ARTICLE
Jonas Håkansson, Brooke L Quinn, Abigail L Shultz, Sharon M Swartz, Aaron J Corcoran
Studying the detailed biomechanics of flying animals requires accurate three-dimensional coordinates for key anatomical landmarks. Traditionally, this relies on manually digitizing animal videos, a labor-intensive task that scales poorly with increasing framerates and numbers of cameras. Here, we present a workflow that combines deep learning-powered automatic digitization with filtering and correction of mislabeled points using quality metrics from deep learning and 3D reconstruction. We tested our workflow using a particularly challenging scenario: bat flight...
April 23, 2024: Annals of the New York Academy of Sciences
#6
JOURNAL ARTICLE
Amir Yari, Paniz Fasih, Mohammad Hosseini Hooshiar, Ali Goodarzi, Seyedeh Farnaz Fattahi
PURPOSE: This study aimed to assess the performance of a deep learning algorithm (YOLOv5) in detecting different mandibular fracture types in panoramic images. METHODS: This study utilized a dataset of panoramic radiographic images with mandibular fractures. The dataset was divided into training, validation, and testing sets, with 60%, 20%, and 20% of the images, respectively. An equal number of control panoramic radiographs, which did not contain any fractures, were also randomly distributed among the three sets...
April 23, 2024: Dento Maxillo Facial Radiology
#7
JOURNAL ARTICLE
Mohammad Elahi, Zahra Ebrahim Soltani, Arya Afrooghe, Elham Ahmadi, Ahmad Reza Dehpour
Our previous research demonstrated that allergic rhinitis could impact behavior and seizure threshold in male mice. However, due to the complex hormonal cycles and hormonal influences on behavior in female mice, male mice are more commonly used for behavioral tests. In this study, we aimed to determine whether these findings were replicable in female mice and to explore the potential involvement of sexual hormones in regulating neuroinflammation in an allergic model. Our results indicate that pain threshold was decreased in female mice with allergic rhinitis and the levels of IL-23/IL-17A/IL-17R were increased in their Dorsal root ganglia...
April 23, 2024: Journal of Neuroimmune Pharmacology: the Official Journal of the Society on NeuroImmune Pharmacology
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JOURNAL ARTICLE
Dawun Jeong, Sunghee Jung, Yeonyee E Yoon, Jaeik Jeon, Yeonggul Jang, Seongmin Ha, Youngtaek Hong, JunHeum Cho, Seung-Ah Lee, Hong-Mi Choi, Hyuk-Jae Chang
To enhance M-mode echocardiography's utility for measuring cardiac structures, we developed and evaluated an artificial intelligence (AI)-based automated analysis system for M-mode images through the aorta and left atrium [M-mode (Ao-LA)], and through the left ventricle [M-mode (LV)]. Our system, integrating two deep neural networks (DNN) for view classification and image segmentation, alongside an auto-measurement algorithm, was developed using 5,958 M-mode images [3,258 M-mode (LA-Ao), and 2,700 M-mode (LV)] drawn from a nationwide echocardiographic dataset collated from five tertiary hospitals...
April 23, 2024: International Journal of Cardiovascular Imaging
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JOURNAL ARTICLE
Xinxin Zhang, Yichen Wang, Xiaojuan Xu, Jie Zhang, Yuying Sun, Mancang Hu, Sicong Wang, Yi Li, Yan Chen, Xinming Zhao
PURPOSE: To investigate the influence of deep learning reconstruction (DLR) on bladder MRI, specifically examination time, image quality, and diagnostic performance of vesical imaging reporting and data system (VI-RADS) within a prospective clinical cohort. METHODS: Seventy participants with bladder cancer who underwent MRI between August 2022 and February 2023 with a protocol containing standard T2-weighted imaging (T2WIS ), standard diffusion-weighted imaging (DWIS ), fast T2WI with DLR (T2WIDL ), and fast DWI with DLR (DWIDL ) were enrolled in this prospective study...
April 23, 2024: Abdominal Radiology
#10
JOURNAL ARTICLE
Katerina Deike, Andreas Decker, Paul Scheyhing, Julia Harten, Nadine Zimmermann, Daniel Paech, Oliver Peters, Silka D Freiesleben, Luisa-Sophie Schneider, Lukas Preis, Josef Priller, Eike Spruth, Slawek Altenstein, Andrea Lohse, Klaus Fliessbach, Okka Kimmich, Jens Wiltfang, Claudia Bartels, Niels Hansen, Frank Jessen, Ayda Rostamzadeh, Emrah Düzel, Wenzel Glanz, Enise I Incesoy, Michaela Butryn, Katharina Buerger, Daniel Janowitz, Michael Ewers, Robert Perneczky, Boris-Stephan Rauchmann, Stefan Teipel, Ingo Kilimann, Doreen Goerss, Christoph Laske, Matthias H Munk, Annika Spottke, Nina Roy, Michael Wagner, Sandra Roeske, Michael T Heneka, Frederic Brosseron, Alfredo Ramirez, Laura Dobisch, Steffen Wolfsgruber, Luca Kleineidam, Renat Yakupov, Melina Stark, Matthias C Schmid, Moritz Berger, Stefan Hetzer, Peter Dechent, Klaus Scheffler, Gabor C Petzold, Anja Schneider, Alexander Effland, Alexander Radbruch
OBJECTIVES: Impaired perivascular clearance has been suggested as a contributing factor to the pathogenesis of Alzheimer disease (AD). However, it remains unresolved when the anatomy of the perivascular space (PVS) is altered during AD progression. Therefore, this study investigates the association between PVS volume and AD progression in cognitively unimpaired (CU) individuals, both with and without subjective cognitive decline (SCD), and in those clinically diagnosed with mild cognitive impairment (MCI) or mild AD...
April 23, 2024: Investigative Radiology
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JOURNAL ARTICLE
State of the Science: Prolonged exposure therapy for the treatment of posttraumatic stress disorder.
Carmen P McLean, Edna B Foa
Prolonged exposure therapy (PE) is a well-established first-line treatment for posttraumatic stress disorder (PTSD) that is based on emotional processing theory. PE has been rigorously evaluated and tested in a large number of clinical trials in many countries covering a wide range of trauma populations. In this review, we summarize the evidence base supporting the efficacy of PE across populations, including adults with sexual assault-related PTSD and mixed trauma-related PTSD, military populations, and adolescents...
April 23, 2024: Journal of Traumatic Stress
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JOURNAL ARTICLE
Li-Da Chen, Ze-Rong Huang, Hong Yang, Mei-Qing Cheng, Hang-Tong Hu, Xiao-Zhou Lu, Ming-De Li, Rui-Fang Lu, Dan-Ni He, Peng Lin, Qiu-Ping Ma, Hui Huang, Si-Min Ruan, Wei-Ping Ke, Bing Liao, Bi-Hui Zhong, Jie Ren, Ming-De Lu, Xiao-Yan Xie, Wei Wang
Background Noninvasive tests can be used to screen patients with chronic liver disease for advanced liver fibrosis; however, the use of single tests may not be adequate. Purpose To construct sequential clinical algorithms that include a US deep learning (DL) model and compare their ability to predict advanced liver fibrosis with that of other noninvasive tests. Materials and Methods This retrospective study included adult patients with a history of chronic liver disease or unexplained abnormal liver function test results who underwent B-mode US of the liver between January 2014 and September 2022 at three health care facilities...
April 2024: Radiology
#13
JOURNAL ARTICLE
H J Pribut, N Kang, Matthew R Roesch
Previous exposure to drugs of abuse produces impairments in studies of reversal learning, delay discounting and response inhibition tasks. While these studies contribute to the understanding of normal decision-making and how it is impaired by drugs of abuse, they do not fully capture how decision-making impacts the ability to delay gratification for greater long-term benefit. To address this issue, we used a diminishing returns task to study decision-making in rats that had previously self-administered cocaine...
April 24, 2024: Behavioural Pharmacology
#14
JOURNAL ARTICLE
Matthew Chan, Toon Verstraelen, Alireza Tehrani, Michelle Richer, Xiaotian Derrick Yang, Taewon David Kim, Esteban Vöhringer-Martinez, Farnaz Heidar-Zadeh, Paul W Ayers
HORTON is a free and open-source electronic-structure package written primarily in Python 3 with some underlying C++ components. While HORTON's development has been mainly directed by the research interests of its leading contributing groups, it is designed to be easily modified, extended, and used by other developers of quantum chemistry methods or post-processing techniques. Most importantly, HORTON adheres to modern principles of software development, including modularity, readability, flexibility, comprehensive documentation, automatic testing, version control, and quality-assurance protocols...
April 28, 2024: Journal of Chemical Physics
#15
JOURNAL ARTICLE
Juan Onetto, Michal Sobczak, Tony Skapetis, Bill Kahler, Olga Tishkina, Geertje Van Gorp, Anne C O'Connell
BACKGROUND/AIM: The International Association of Dental Traumatology (IADT) is considered the foremost authority in Dental Traumatology. Fellowship status was introduced in 2015 and is considered an international standard of excellence. The Fellowship Committee of the IADT believed it was essential to survey members seeking information on the benefits of the IADT Fellowship and potential considerations for future development. This survey aimed to explore the perceptions of members of IADT surrounding the fellowship process in terms of interest, accessibility, equality, perceived prestige, and value to the membership...
April 23, 2024: Dental Traumatology: Official Publication of International Association for Dental Traumatology
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JOURNAL ARTICLE
Laura S Kraemer, Joseph Lopreiato, Haana McMurray, Theepica Jeyarajah, Rachel Dampman, Sorana Raiciulescu, Gerardo Capo Dosal, Edward Jaffe, Julia Switzer, Mark Bowyer
INTRODUCTION: Surgical cricothyroidotomy (SC) is a vital skill that combat first responders must master as airway obstruction is the third most preventable cause of death on the battlefield. Degradation of skills over time is a known problem, and there is inadequate knowledge regarding the rate of SC skill retention. Our prior study showed that simulation-based mastery learning was effective in training 89 novices how to reliably perform an en route SC to mastery performance standards...
April 23, 2024: Military Medicine
#17
JOURNAL ARTICLE
Matthew Davis, Kit Simpson, Vanessa Diaz, Alexander V Alekseyenko
PURPOSE: The objective of this study is to describe patterns in barriers to breast cancer screening uptake with the end goal of improving screening adherence and decreasing the burden of mortality due to breast cancer. This study looks at social determinants of health and their association to screening and mortality. It also investigates the extent that models trained on county data are generalizable to individuals. METHODS: County level screening uptake and age adjusted mortality due to breast cancer are combined with the Centers for Disease Controls Social Vulnerability Index (SVI) to train a model predicting screening uptake rates...
March 2024: Fortune J Health Sci
#18
JOURNAL ARTICLE
Dalia Albahari
BACKGROUND: Learning clinical reasoning is less effective in isolation of clinical environments because contextual factors are a significant component in the clinical reasoning process. This study investigated the differences in opinions between novice and expert clinicians on learning clinical reasoning in the workplace. MATERIALS AND METHODS: The author used a cross-sectional online survey design to investigate the perceived learning of six clinical reasoning skills in 13 learning opportunities...
2024: Qatar Medical Journal
#19
JOURNAL ARTICLE
Self-reported cultural competence among Czech and Slovakian nurses: A comparative correlation study.
Martin Červený, Valérie Tóthová
AIM: This study aimed to compare the level of cultural competence among nurses working in clinical practice in Slovakia and the Czech Republic. BACKGROUND: Demographic changes have greatly affected the health sector in Slovakia and the Czech Republic. By identifying the level of nurses' cultural competence, many of the complications encountered in caring for patients from different cultures can be avoided. However, few studies have explored the cultural competence of nurses in clinical practice in these countries...
April 23, 2024: International Nursing Review
#20
JOURNAL ARTICLE
Sixtine Fleury, Rhonda Kolaric, Justin Espera, Quan Ha, Jacquelyn Tomaio, Ulrik Gether, Andreas Toft Sørensen, Susana Mingote
Dopamine neurons signal the salience of environmental stimuli and influence learning, although it is less clear if these neurons also determine the salience of memories. Ventral tegmental area (VTA) dopamine neurons increase their firing in the presence of new objects and reduce it upon repeated, inconsequential exposures, marking the shift from novelty to familiarity. This study investigates how dopamine neuron activity during repeated familiar object exposure affects an animal's preference for new objects in a subsequent novel object recognition (NOR) test...
April 23, 2024: European Journal of Neuroscience
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