Signatures of H3K4me3 modification predict cancer immunotherapy response and identify a new immune checkpoint-SLAMF9 by Tao Fan, Chu Xiao, Ziqin Deng, Shuofeng Li, He Tian, Yujia Zheng, Bo Zheng, Chunxiang Li, Jie He

“…Using the principal component analysis (PCA) of H3K4me3-related patterns, we constructed a H3K4me3 risk score (H3K4me3-RS) system. The deep learning analysis using 12,159 cancer samples from 26 cancer types and 725 cancer samples from 5 immunotherapy cohorts revealed that H3K4me3-RS was significantly correlated with cancer immune tolerance and sensitivity. …”
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AI prediction model for endovascular treatment of vertebrobasilar occlusion with atrial fibrillation by Zhi-Xin Huang, Andrea M. Alexandre, Alessandro Pedicelli, Xuying He, Quanlong Hong, Yongkun Li, Ping Chen, Qiankun Cai, Aldobrando Broccolini, Luca Scarcia, Serena Abruzzese, Carlo Cirelli, Mauro Bergui, Andrea Romi, Erwah Kalsoum, Giulia Frauenfelder, Grzegorz Meder, Simona Scalise, Maria Porzia Ganimede, Luigi Bellini, Bruno Del Sette, Francesco Arba, Susanna Sammali, Andrea Salcuni, Sergio Lucio Vinci, Giacomo Cester, Luisa Roveri, Xianjun Huang, Wen Sun

“…While 45.1% achieved favorable outcomes at 90 days, our advanced machine learning approach unveiled subtle interaction effects among clinical variables not captured by traditional statistical methods. …”
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QUIET WARRIOR – Rationale and design: An ancillary study to the Women's IschemiA TRial to Reduce Events in Nonobstructive CAD (WARRIOR) by Osama Dasa, Eileen Handberg, Damini Dey, Pinaki Sarder, Margaret C. Lo, Balaji K. Tamarappoo, Steven M. Smith, Leslee J. Shaw, C. Noel Bairey Merz, Carl J. Pepine

“…Advanced imaging techniques and machine-learning models will be employed to quantify plaque features and predict clinical outcomes. …”
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Longitudinal exploration of cancer-related cognitive impairment in patients with newly diagnosed aggressive lymphoma: protocol for a feasibility study by Vincent Dore, Christopher C Rowe, Meinir Krishnasamy, Haryana Dhillon, Adam K Walker, Karla Gough, Priscilla Gates, Carlene Wilson, Eliza Hawkes, Yuliya Perchyonok, Janette L Vardy, Michiel de Ruiter

“…All patients will be assessed for self-reported cognitive difficulties and objective cognitive function using Stroop Colour and Word, Trail Making Test Part A and B, Hopkins Verbal Learning Test-Revised, Controlled Oral Word Association and Digit Span. …”
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Protocol for a multi-domain scoping review to identify measures of decision-making ability in an ageing population by Janel Hanmer, Richard Gershon, Sandra Weintraub, Zahra Hosseinian, Emily H. Ho, Berivan Ece, Miriam A. Novack, Sarah Pila, Tatiana Karpouzian-Rogers, Molly A Mather, Elizabeth McManus Dworak, Patricia Bucko, Aaron James Kaat, S. Duke Han, Peter Lichtenberg, Corinne H Miller

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Factors associated with early childhood development: results from the Brazilian National Survey on Child Nutrition (ENANI-2019) by Gilberto Kac, Nadya Helena Alves-Santos, Dayana Rodrigues Farias, Nathalia Cristina Freitas-Costa, Raquel Scincaglia, Paula Normando, Inês Rugani, Elisa Maria de Aquino Lacerda, Sandra Crispim, Alexandra Valeria Maria Brentani, Claudia Regina Lindgren Alves

“…For children aged 36–59 months, attendance to private daycare/school (β=0.08; p<0.01) was positively associated with DQ, and small for gestational age at birth (β=−0.05; p=0.01) and access to public health services (no-primary care) (β=−0.07; p<0.01) were inversely associated with DQ.Conclusions Adverse health, nutrition and learning factors predicted the ECD, demonstrating an inequitable environment for Brazilian children. …”
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Artificial intelligence-assisted clinical decision support for childhood asthma management: A randomized clinical trial. by Hee Yun Seol, Pragya Shrestha, Joy Fladager Muth, Chung-Il Wi, Sunghwan Sohn, Euijung Ryu, Miguel Park, Kathy Ihrke, Sungrim Moon, Katherine King, Philip Wheeler, Bijan Borah, James Moriarty, Jordan Rosedahl, Hongfang Liu, Deborah B McWilliams, Young J Juhn

“…<h4>Measurements</h4>Intervention was a quarterly A-GPS report to clinicians including relevant clinical information for asthma management from EHRs and machine learning-based prediction for risk of asthma exacerbation (AE). …”
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Empirical estimation of saturated soil-paste electrical conductivity in the EU using pedotransfer functions and Quantile Regression Forests: A mapping approach based on LUCAS topso... by Calogero Schillaci, Simone Scarpa, Felipe Yunta, Aldo Lipani, Fernando Visconti, Gábor Szatmári, Kitti Balog, Triven Koganti, Mogens Greve, Giulia Bondi, Georgios Kargas, Paraskevi Londra, Fuat Kaya, Giuseppe Lo Papa, Panos Panagos, Luca Montanarella, Arwyn Jones

“…In this work, using the LUCAS 2018 dataset, we provide an empirically-derivedpedotransfer function to convert diluted EC1:5 to saturated ECe using the LUCAS soil texture and soil organic carbon, and a framework for ECe mapping with a machine-learning algorithm named Quantile Regression Forest. …”
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Consecutive prediction of adverse maternal outcomes of preeclampsia, using the PIERS-ML and fullPIERS models: A multicountry prospective observational study. by Guiyou Yang, Tünde Montgomery-Csobán, Wessel Ganzevoort, Sanne J Gordijn, Kimberley Kavanagh, Paul Murray, Laura A Magee, Henk Groen, Peter von Dadelszen

“…., the PIERS Machine Learning [PIERS-ML] model, and the logistic regression-based fullPIERS model) accurately identify individuals at greatest or least risk of adverse maternal outcomes within 48 h following admission. …”
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Strategies to Promote ResiliencY (SPRY): a randomised embedded multifactorial adaptative platform (REMAP) clinical trial protocol to study interventions to improve recovery after s... by Derek C Angus, Jennifer Holder-Murray, Katherine Moll Reitz, Christopher W Seymour, Jennifer Vates, Melanie Quintana, Kert Viele, Michelle Detry, Michael Morowitz, Alison Morris, Barbara Methe, Jason Kennedy, Brian Zuckerbraun, Timothy D Girard, Oscar C Marroquin, Stephen Esper, Anne B Newman, Scott Berry, Matthew Neal

“…We describe a randomised, embedded, multifactorial, adaptative platform (REMAP) trial to investigate multiple perioperative interventions, the first of which is metformin and selected for its anti-inflammatory and anti-ageing properties beyond its traditional blood glucose control features.Methods and analysis Within a multihospital, single healthcare system, the Core Protocol for Strategies to Promote ResiliencY (SPRY) will be embedded within both the electronic health record (EHR) and the healthcare culture generating a continuously self-learning healthcare system. Embedding reduces the administrative burden of a traditional trial while accessing and rapidly analysing routine patient care EHR data. …”
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Qualitative evaluation of the Rehabilitation Exercise and psycholoGical support After COVID-19 InfectioN (REGAIN) randomised controlled trial (RCT): ‘you are not alone’ by Gordon McGregor, Susanne Finnegan, Martin Underwood, Joyce Yeung, James Mason, Peter Heine, Nigel Edwards, Julie Bruce, Kate Seers, Harbinder Kaur Sandhu, Helen Atherton, Sharisse Alleyne, Katie Booth, Ranjit Lall, Vivien P Nichols, Stuart Ennis, Scott McGuire, Rachel Potter, Jessica Smith, Chen Ji, Shilpa Patel, Henry Nwankwo, Kate Evans, Susie Hennings, Alastair Canaway, Grace Lobley, David Mcwilliams, Christina Jones, Emma Padfield, David Montgomery, Beatriz Lara, Becky Haley, Francesca Denton, Bartholomew Sheehan, Mariam Ratna, Elaine Fairbrother, Zoe Noakes, Bogdan Zutic, Lee Austin, Tom Forsyth, Anne Bush, Alan Bush, Patrick Sawdon, Jonathon Prosser, Lee Tompkins, Jonathon Guck, Danielle Hale, Juwairia Said, Georgie Ray, Rowena Williams, Gail Evans, Thillini Hettiarachchi, Abeesh Panicker

“…The group sessions of both exercise and psychological support were valued by participants, working together, and learning from each other in the face of a new disease within a global pandemic.…”
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Penerapan Intelligent Geographic Information System untuk Deteksi Kecanduan Game by Anastasya Latubessy, Ahmad Jazuli, Rina Fiati

“…Previous research has shown a negative correlation between game addiction and the learning process. Reviewing this, parents need to be aware of the pattern of children's game play. …”
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Toward accurate prediction of carbon dioxide (CO2) compressibility factor using tree-based intelligent schemes (XGBoost and LightGBM) and equations of state by Behnam Amiri-Ramsheh, Aydin Larestani, Saeid Atashrouz, Elnaz Nasirzadeh, Meriem Essakhraoui, Ali Abedi, Mehdi Ostadhassan, Ahmad Mohaddespour, Abdolhossein Hemmati-Sarapardeh

“…In this study, two powerful and robust tree-based machine learning (ML) algorithms, namely light gradient boosted machine (LightGBM) and extreme gradient boosting (XGBoost) were utilized to precisely estimate CO2 Z-factor. …”
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Mental health phenotypes of well-controlled HIV in Uganda by Leah H. Rubin, Leah H. Rubin, Leah H. Rubin, Leah H. Rubin, Kyu Cho, Jacob Bolzenius, Julie Mannarino, Rebecca E. Easter, Raha M. Dastgheyb, Aggrey Anok, Stephen Tomusange, Deanna Saylor, Maria J. Wawer, Noeline Nakasujja, Gertrude Nakigozi, Robert Paul

“…We leverage the analytic strengths of machine learning combined with inferential methods to identify novel MH phenotypes among PWH and the underlying explanatory features.MethodsA total of 277 PWH (46% female, median age = 44; 93% virally suppressed [&lt;50copies/mL]) were included in the analyses. …”
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Artificial intelligence can help individualize Wilms tumor treatment by predicting tumor response to preoperative chemotherapy by Ahmed Nashat, Ahmed Alksas, Rasha T. Aboulelkheir, Ahmed Elmahdy, Sherry M. Khater, Hossam M. Balaha, Israa Sharaby, Mohamed Shehata, Mohammed Ghazal, Salama Abd El-Wadoud, Ayman El-Baz, Ahmed Mosbah, Ahmed Abdelhalim

“…Favorable volumetric and histologic responses were achieved in 46 tumors (73.0%) and 38 tumors (60.3%), respectively. Among machine learning classifiers, support vector machine had the best diagnostic performance with an accuracy, sensitivity, and specificity of 95.24%, 95.65%, and 94.12% for volumetric and 84.13%, 89.47%, 88% for histologic response prediction. …”
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Prompt-based three-dimensional tooth segmentation method based on pre-trained SAM(基于预训练SAM的提示式三维牙齿分割方法) by 刘复昌(LIU Fuchang), 蔡煜晨(CAI Yuchen), 缪永伟(MIAO Yongwei), 范然(FAN Ran)

“…Currently, most studies employ supervised learning techniques to train networks on three-dimensional tooth data to perform annotation tasks. …”
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Comparative analysis of ChatGPT and Gemini (Bard) in medical inquiry: a scoping review by Fattah H. Fattah, Fattah H. Fattah, Abdulwahid M. Salih, Abdulwahid M. Salih, Ameer M. Salih, Ameer M. Salih, Saywan K. Asaad, Saywan K. Asaad, Abdullah K. Ghafour, Rawa Bapir, Rawa Bapir, Rawa Bapir, Berun A. Abdalla, Berun A. Abdalla, Snur Othman, Sasan M. Ahmed, Sasan M. Ahmed, Sabah Jalal Hasan, Yousif M. Mahmood, Fahmi H. Kakamad, Fahmi H. Kakamad, Fahmi H. Kakamad

“…IntroductionArtificial intelligence and machine learning are popular interconnected technologies. AI chatbots like ChatGPT and Gemini show considerable promise in medical inquiries. …”
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Educational outcomes of children with major congenital anomalies: Study protocol for a population-based cohort study using linked hospital and education data from England [version... by Ruth Gilbert, Ania Zylbersztejn, Bianca De Stavola, Ayana Cant, Laura Gimeno, Katie Harron, Kate Lewis, Joachim Tan, Pia Hardelid, Vincent Nguyen

“…Children with CAs are at greater risk of lower educational attainment compared with their peers, which could be due to learning disabilities, higher rates of ill-health and school absences, or lack of adequate educational support. …”
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An atmospheric correction method for Himawari-8 imagery based on a multi-layer stacking algorithm by Menghui Wang, Donglin Fan, Hongchang He, You Zeng, Bolin Fu, Tianlong Liang, Xinyue Zhang, Wenhan Hu

“…For comparative analysis, a near-infrared–shortwave infrared AC method and a general machine learning AC method were also implemented. Model evaluation and validation were performed using a test subset of simulated data and in-situ datasets. …”
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Enriched environment rescues bisphenol A induced anxiety-like behavior and cognitive impairment by modulating synaptic plasticity by Jiong Li, Guangyin Yu, Laijian Wang, Wenjun Zhang, Wenya Ke, Yifei Li, Danlei Liu, Keman Xie, Yuanyuan Xu, Caihui Cha, Guoqing Guo, Jifeng Zhang

“…Additionally, spatial and learning memory cognitive impairments were observed in Y-maze and water maze tests. …”
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