Optimizing Automated Hematoma Expansion Classification from Baseline and Follow-Up Head Computed Tomography by Anh T. Tran, Dmitriy Desser, Tal Zeevi, Gaby Abou Karam, Julia Zietz, Andrea Dell’Orco, Min-Chiun Chen, Ajay Malhotra, Adnan I. Qureshi, Santosh B. Murthy, Shahram Majidi, Guido J. Falcone, Kevin N. Sheth, Jawed Nawabi, Seyedmehdi Payabvash

“…In this study, we combined a tandem deep-learning classification model with automated segmentation to generate probability measures for false HE classifications. …”
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Targeting early tau pathology: probiotic diet enhances cognitive function and reduces inflammation in a preclinical Alzheimer’s model by Cassandra M. Flynn, Tamunotonye Omoluabi, Alyssa M. Janes, Emma J. Rodgers, Sarah E. Torraville, Brenda L. Negandhi, Timothy E. Nobel, Shyamchand Mayengbam, Qi Yuan

“…The enhancement in gut microbiomes was associated with enhanced spatial learning (p < 0.05), reduced inflammation indexed by Iba-1 (F 1,25 = 5.284, p = 0.030) and CD-68 (F 1,26 = 8.441, p = 0.007) expression, and inhibited GSK-3β in female rats (p < 0.01 compared to control females). …”
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Personalized prediction of glycemic responses to food in women with diet-treated gestational diabetes: the role of the gut microbiota by Polina V. Popova, Artem O. Isakov, Anastasiia N. Rusanova, Stanislav I. Sitkin, Anna D. Anopova, Elena A. Vasukova, Alexandra S. Tkachuk, Irina S. Nemikina, Elizaveta A. Stepanova, Angelina I. Eriskovskaya, Ekaterina A. Stepanova, Evgenii A. Pustozerov, Maria A. Kokina, Elena Y. Vasilieva, Lyudmila B. Vasilyeva, Soha Zgairy, Elad Rubin, Carmel Even, Sondra Turjeman, Tatiana M. Pervunina, Elena N. Grineva, Omry Koren, Evgeny V. Shlyakhto

“…The study involved 105 pregnant women (77 with GDM, 28 healthy), who underwent continuous glucose monitoring (CGM) for 7 days, provided food diaries, and gave stool samples for microbiome analysis. Machine learning models were created using CGM data, meal content, lifestyle factors, biochemical parameters, and microbiota data (16S rRNA gene sequence analysis). …”
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Chemical Composition, In Vivo, and In Silico Molecular Docking Studies of the Effect of <i>Syzygium aromaticum</i> (Clove) Essential Oil on Ochratoxin A-Induced Acute Neurotoxicity by Mostapha Brahmi, Djallal Eddine H. Adli, Imane Kaoudj, Faisal K. Alkholifi, Wafaa Arabi, Soumia Sohbi, Kaddour Ziani, Khaled Kahloula, Miloud Slimani, Sherouk Hussein Sweilam

“…The neurobehavioral analysis using several behavioral testing techniques, such as the forced swimming, the dark/light test, the Morris water maze, and the open field test, clearly revealed that OTA exposure causes neurobehavioral disorders, including decreased locomotor activity, a reduced willingness to explore the environment, reflecting a state of stress, anxiety and depression, as well as impaired memory and learning. In addition, OTA intoxication has been associated with metabolic disturbances such as hyperglycemia and hypercortisolemia. …”
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Predictive modelling and identification of critical variables of mortality risk in COVID-19 patients by Olawande Daramola, Tatenda Duncan Kavu, Maritha J. Kotze, Jeanine L. Marnewick, Oluwafemi A. Sarumi, Boniface Kabaso, Thomas Moser, Karl Stroetmann, Isaac Fwemba, Fisayo Daramola, Martha Nyirenda, Susan J. van Rensburg, Peter S. Nyasulu

“…Aside from clinical methods, artificial intelligence (AI)-based solutions such as machine learning (ML) models have been employed in treating COVID-19 cases. …”
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Adapting the Technology Acceptance Model to Examine the Use of Information Communication Technologies and Loneliness Among Low-Income, Older Asian Americans: Cross-Sectional Survey... by Pauline DeLange Martinez, Daniel Tancredi, Misha Pavel, Lorena Garcia, Heather M Young

“…PU combined 2 items assessing the usefulness of technology for social connection and learning and accounted for a 12.44% (1.49/12) variance. …”
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Molecular mechanisms of aflatoxin neurotoxicity and potential neuroprotective agents by Chongshan Dai, Erjie Tian, Hui Li, Subhajit Das Gupta, Zhihui Hao, Zhanhui Wang, Tony Velkov, Jianzhong Shen

“…Animal studies indicated that AFB1 exposure could induce abnormal behavioral changes, including anxiety, lethargy disorders, depression-like behavior, cognitive, learning and memory defects, and decreased feeding behavior. …”
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Federally qualified health center patients’ experiences with remote patient monitoring as part of telehealth services for self-measured blood pressure monitoring by Natalia I. Heredia, Maria E. Fernandez, Ella R. Garza, Jabria Pittman, Fernanda Velasco-Huerta, Tracy L. Judd, Jocelyn Hunyadi, Elvis Longanga Diese, Deevakar Rogith, William B. Perkison, Susan H. Fenton

“…Three themes emerged from open-ended data: perceived ease of learning and using mobile patient portal for SMBP, perceived benefits of using mobile patient portal for SMBP, and intentions to continue using the mobile patient portal for SMBP. …”
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Predictive role of SLC1A5 in neuroblastoma prognosis and immunotherapy by Jian Cheng, Miaomiao Sun, Xiao Dong, Yang Yang, Xiaohan Qin, Xing Zhou, Yongcheng Fu, Yuanyuan Wang, Jingyue Wang, Da Zhang

“…A prognostic signature, SRPS, was constructed and validated using machine-learning approaches. Immune infiltration analysis was performed to evaluate the tumor immune microenvironment. …”
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Implementation of prehospital point-of-care ultrasound using a novel continuous feedback approach in a UK helicopter emergency medical service by Salman Naeem, Shadman Aziz, Thomas Hirst, Johannes Strobel, Jamin M. Mulvey, Ailidh Lang, Jankee Patel, Alexander Smith, Ka Jun Cheng, Michael Palmer, Jonas Schlautmann, Michael D. Christian, Daniel Nevin

“…They were graded in adequacy, agreement between reviewer and clinician was recorded and fed back to the clinicians allowing continuous feedback learning. In-hospital diagnosis was sought for patients having the full Pump, Pleura and Pouring blood (PPPB) protocol. …”
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Shift work schedules alter immune cell regulation and accelerate cognitive impairment during aging by Karienn A. de Souza, Morgan Jackson, Justin Chen, Jocelin Reyes, Judy Muayad, Emma Tran, William Jackson, M. Karen Newell-Rogers, David J. Earnest

“…Abstract Background Disturbances of the sleep-wake cycle and other circadian rhythms typically precede the age-related deficits in learning and memory, suggesting that these alterations in circadian timekeeping may contribute to the progressive cognitive decline during aging. …”
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Supporting teams with designing for dissemination and sustainability: the design, development, and usability of a digital interactive platform by Maura M. Kepper, Allison J. L’Hotta, Thembekile Shato, Bethany M. Kwan, Russell E. Glasgow, Douglas Luke, Andrea K. Graham, Ana A. Baumann, Ross C. Brownson, Brad Morse

“…Conclusions This is a first of its kind tool that supports research teams in learning about and explicitly applying D4DS to their work. …”
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Multicultural values: meeting point of two forces in developing Islamic education by Dwi Mariyono

“…This integration creates an inclusive learning environment conducive to the development of entrepreneurial skills, innovation and ethical leadership. …”
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Multilevel determinants of racial/ethnic disparities in severe maternal morbidity and mortality in the context of the COVID-19 pandemic in the USA: protocol for a concurrent triang... by Bankole Olatosi, Jiajia Zhang, Xiaoming Li, Chen Liang, Jihong Liu, Peiyin Hung, Shan Qiao, Berry A Campbell, Myriam E Torres, Neset Hikmet

“…Non-Hispanic black and Hispanic pregnant women appear to have disproportionate SARS-CoV-2 infection and death rates.Methods and analysis We will use the socioecological framework and employ a concurrent triangulation, mixed-methods study design to achieve three specific aims: (1) examine the impacts of the COVID-19 pandemic on racial/ethnic disparities in severe maternal morbidity and mortality (SMMM); (2) explore how social contexts (eg, racial/ethnic residential segregation) have contributed to the widening of racial/ethnic disparities in SMMM during the pandemic and identify distinct mediating pathways through maternity care and mental health; and (3) determine the role of social contextual factors on racial/ethnic disparities in pregnancy-related morbidities using machine learning algorithms. We will leverage an existing South Carolina COVID-19 Cohort by creating a pregnancy cohort that links COVID-19 testing data, electronic health records (EHRs), vital records data, healthcare utilisation data and billing data for all births in South Carolina (SC) between 2018 and 2021 (&gt;200 000 births). …”
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ANN-based two hidden layers computational procedure for analysis of heat transport dynamics in polymer-based trihybrid Carreau nanofluid flow over needle geometry by Adil Darvesh, Fethi Mohamed Maiz, Basma Souayeh, Luis Jaime Collantes Santisteban, Hakim AL. Garalleh, Afnan Al Agha, Lucerito Katherine Ortiz García, Nicole Anarella Sánchez-Miranda

“…Their advantages in handling nonlinearities and modeling high-dimensional data through integrating physical laws make them far superior to simpler machine learning and other traditional techniques, despite requiring greater data and computational resources. …”
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Intelligent prediction method of virtual network function resource capacity for polymorphic network service slicing by Julong LAN, Di ZHU, Dan LI

“…With the help of machine learning algorithms, the VNF resource capacity demand prediction method VNFPre proposed for polymorphic network scenarios,it can judge the future VNF resource capacity demand of network slices, and provide a priori information for the placement and mapping of VNFs carried by network slices.…”
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Factors and Reasons Associated with Hesitating to Seek Care for Migraine: Results of the OVERCOME (US) Study by Robert E. Shapiro, Eva Jolanda Muenzel, Robert A. Nicholson, Anthony J. Zagar, Michael L. Reed, Dawn C. Buse, Susan Hutchinson, Sait Ashina, Eric M. Pearlman, Richard B. Lipton

“…Methods The web-based OVERCOME (US) survey study identified adults with active migraine in a demographically representative US sample who answered questions about hesitating to seek care from a healthcare provider for migraine and reasons for hesitating. Supervised machine learning (random forest, least absolute shrinkage and selection operator) identified factors associated with hesitation; logistic regression models assessed association of factors on hesitation. …”
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Gambaran Pengetahuan dan Sikap Mahasiswa Fakultas Kedokteran Universitas Andalas tentang Rokok by Yosantaraputra ., Yanwirasti ., Abdiana .

“…From these resultsit can be concluded that the knowledge of students of the Faculty of Medicine, University of Andalas in average category and attitude of students of the Facultyof Medicine, University of Andalas are ingood category.It is recommended to students of the Faculty of Medicine, University of Andalas in order tofind out about nicotine and consequently independently in accordance with the PBL learning systems, as well as the enactment ofsmoke-fre elegislation in the Faculty of Medicine, University ofAndalas.…”
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Characteristics and outcomes of women using emergency medical services for third-trimester pregnancy-related problems in India: a prospective observational study by Jennifer A Newberry, Corey B Bills, Elizabeth A Pirrotta, Matthew C Strehlow, G V Ramana Rao, Hyeyoun (Elise) Min, Ann E Evensen, Lawrence Leeman, S V Mahadevan

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Identification of Health Needs in Ukrainian Refugees Seen in a Primary Care Facility in Tenerife, Spain by Willian-Jesús Martín-Dorta, Cristo-Manuel Marrero-González, Eva-Lourdes Díaz-Hernández, Pedro-Ruymán Brito-Brito, Domingo-Ángel Fernández-Gutiérrez, Oxana-Migalievna Rebryk-De Colichón, Ana-Isabel Martín-García, Estrella Pavés-Lorenzo, María-Candelaria Rodríguez-Santos, Juan-Francisco García-Cabrera, Janet Núnez-Marrero, Alfonso-Miguel García-Hernández

“…The primary social demands include seeking employment, learning the language, and increasing support groups among Ukrainians themselves. …”
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