Spatial Vibration Characteristics and Damage Identification of Toppling Dangerous Rock Mass by Chen ZHAO, Mowen XIE, Yan DU, Zhengjun HUANG, Zheng HE, Guang LU

“…Objective Currently, most studies on kinetic indices that reflect the damage of dangerous rock masses analyze the vibration characteristics in a single direction. …”
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Interpersonal counselling for adolescent depression delivered by youth mental health workers without core professional training: the ICALM feasibility RCT by Jon Wilson, Viktoria Cestaro, Eirini Charami-Roupa, Timothy Clarke, Aoife Dunne, Brioney Gee, Sharon Jarrett, Thando Katangwe-Chigamba, Andrew Laphan, Susie McIvor, Richard Meiser-Stedman, Jamie Murdoch, Thomas Rhodes, Carys Seeley, Lee Shepstone, David Turner, Paul Wilkinson

“…Participants were randomised in a 1 : 1 ratio using a stochastic minimisation algorithm to minimise imbalance between groups in baseline symptom severity, gender and study site to receive either IPC-A or TAU. …”
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Employing artificial intelligence for optimising antibiotic dosages in sepsis on intensive care unit: a study protocol for a prospective observational study (KI.SEP) by Tim Rahmel, Michael Adamzik, Hartmuth Nowak, Lars Bergmann, Björn Koos, Martin Eisenacher, Barbara Sitek, Britta Marko, Lars Palmowski, Andrea Witowski, Katharina Rump, Julia Bandow, Patrick Günther

“…Our two-way approach involves creating two distinct algorithms: the first focuses on predictive accuracy and generalisability using routine clinical parameters, while the second leverages an extended dataset including a plethora of factors currently insufficiently explored and not available in standard clinical practice but may help to enhance precision. …”
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Targeted urinary metabolomics combined with machine learning to identify biomarkers related to central carbon metabolism for IBD by Miao-Lin Lei, Guan-Wei Bi, Xiao-Lin Yin, Xiao-Lin Yin, Yue Wang, Yue Wang, Yue Wang, Zi-Ru Sun, Zi-Ru Sun, Zi-Ru Sun, Xin-rui Guo, Hui-peng Zhang, Xiao-han Zhao, Feng Li, Feng Li, Yan-Bo Yu

“…Diagnostic models were constructed using six machine learning algorithms, and their performance was evaluated by cross-validated area under the receiver operating characteristic curve (AUC). …”
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A systematic review of data privacy in Mobility as a Service (MaaS) by Zineb Garroussi, Antoine Legrain, Sébastien Gambs, Vincent Gautrais, Brunilde Sansò

“…This systematic review identifies key data privacy concerns, evaluates current privacy-preserving technologies, and explores the role of regulatory frameworks in ensuring user privacy in MaaS systems. …”
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Predicting chronic pain using wearable devices: a scoping review of sensor capabilities, data security, and standards compliance by Johannes C. Ayena, Johannes C. Ayena, Amina Bouayed, Amina Bouayed, Myriam Ben Arous, Myriam Ben Arous, Youssef Ouakrim, Youssef Ouakrim, Karim Loulou, Karim Loulou, Darine Ameyed, Isabelle Savard, Leila El Kamel, Neila Mezghani, Neila Mezghani

“…Data extraction focused on device types, sensor quality, compliance with health standards, and the predictive algorithms employed.ResultsWearable devices show promise in correlating physiological markers with CP, but few studies integrate predictive models. …”
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Development of prediction models for screening depression and anxiety using smartphone and wearable-based digital phenotyping: protocol for the Smartphone and Wearable Assessment f... by Sujin Kim, Ah Young Kim, Yu-Bin Shin, Seonmin Kim, Min-Sup Shin, Jinhwa Choi, Kyung Lyun Lee, Jisu Lee, Sangwon Byun, Heon-Jeong Lee, Chul-Hyun Cho

“…The primary outcome will be the development of machine-learning algorithms to predict depression and anxiety based on these digital biomarkers. …”
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Seasonal habitat suitability and distribution patterns of Mediterranean fin whales by E. Papale, A. Arcangeli, A. Azzellino, M. Bellingeri, G. Bergamini, G. Buscaino, G. Calogero, A. Cañadas, L. David, R. De Stephanis, N. Di-Méglio, C. Lanfredi, C. Giacoma, G. Gnone, B. Mussi, D.S. Pace, L. Pintore, L. Pireddu, J.M. Salazar-Sierra, P. Tepsich, B. Violi, A. Giovannini

“…In this study, the Maximum Entropy algorithm was applied to seasonal Species Distribution Models (SDM) to identify the habitat preferences of fin whales and the potential ecological drivers, over a 20-year period in the Western and Central Mediterranean Sea. …”
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Viral replication modulated by hallmark conformational ensembles: how AlphaFold-predicted features of RdRp folding dynamics combined with intrinsic disorder-mediated function enabl... by Rachid Tahzima, Rachid Tahzima, Rachid Tahzima, Rachid Tahzima, Justine Charon, Adrian Diaz, Kris De Jonghe, Sebastien Massart, Thierry Michon, Wim Vranken, Wim Vranken, Wim Vranken, Wim Vranken

“…Overall, tapping into the current knowledge of RdRp conformational heterogeneity will serve further RNA virus discovery as similarities in the global RdRp landscape emerge with more clarity.…”
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The interaction between temperature and precipitation on the potential distribution range of Betula ermanii in the alpine treeline ecotone on the Changbai Mountain by Yu Cong, Yongfeng Gu, Wen J. Wang, Lei Wang, Zhenshan Xue, Yingyi Chen, Yinghua Jin, Jiawei Xu, Mai-He Li, Hong S. He, Ming Jiang

“…Hence, we used a GF-2 satellite image, along with bioclimatic and topographic variables, to develop an ensemble suitable habitat model based on the species distribution modeling algorithms in Biomod2. We investigated the distribution of suitable habitats for B. ermanii under three climate change scenarios (i.e., low (SSP126), moderate (SSP370) and extreme (SSP585) future emission trajectories) between two consecutive time periods (i.e., current–2055, and 2055–2085). …”
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Modeling the effects of climate change scenarios on the potential distribution of Vespa crabro Linnaeus, 1758 (Hymenoptera: Vespidae) in a Mediterranean biodiversity hotspot by Erika Bazzato, Arturo Cocco, Emanuele Salaris, Ignazio Floris, Alberto Satta, Michelina Pusceddu

“…The individual models were weighted based on spatial cross-validation performance and combined to obtain the ensemble model.Performance varied among 150 individual models (3 algorithms × 10 replicates × 5 folds), depending on the algorithms, replicates, and subsets selected for training and testing. …”
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Suspicion and referral of patients with transthyretin amyloid cardiomyopathy: Recommendations by a Portuguese multidisciplinary expert panel by Dulce Brito, João Agostinho, Carlos Aguiar, Sílvia Aguiar Rosa, Nuno Cardim, Cândida Fonseca, Nuno Marques, Pedro Moraes Sarmento, Patrícia Rodrigues, Jonathan Santos, Maria João Vidigal Ferreira, Olga Azevedo

“…To ensure timely diagnosis, a multidisciplinary panel of Portuguese experts, including cardiologists, internal medicine specialists, and general practitioners, have developed a national consensus to aid physicians in enhancing the referral of patients with suspicion of ATTR-CM in Portugal.A structured approach was used to develop the consensus: (1) an online survey aimed at identifying clinical red flags, patient journeys, and diagnostic tools related to ATTR-CM; (2) a face-to-face roundtable meeting where the survey findings were discussed and a consensus was reached on referral and diagnostic algorithms for ATTR-CM in Portugal; and (3) critical review of the proposed algorithms.The referral and diagnostic algorithms for ATTR-CM in Portugal were developed considering current recommendations, but also the existence of a nationwide network of specialized cardiomyopathy clinics and national reference centers for familial amyloid polyneuropathy due to the endemic p.V50M variant.This collaborative effort aims to enhance awareness, facilitate timely referrals and improve early diagnosis, ultimately ensuring better management of ATTR-CM patients in Portugal. …”
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The application of artificial intelligence in upper gastrointestinal cancers by Xiaoying Huang, Minghao Qin, Mengjie Fang, Zipei Wang, Chaoen Hu, Tongyu Zhao, Zhuyuan Qin, Haishan Zhu, Ling Wu, Guowei Yu, Francesco De Cobelli, Xuebin Xie, Diego Palumbo, Jie Tian, Di Dong

“…Furthermore, we separately reviewed the application of AI technology in the aforementioned aspects for both esophageal and gastric cancers. Finally, the current limitations and challenges faced in the field of upper gastrointestinal cancers were summarized, and explorations were conducted on the selection of AI algorithms in various scenarios, the popularization of early screening, the clinical applications of AI, and large multimodal models.…”
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Deep learning radiomics nomogram predicts lymph node metastasis in laryngeal squamous cell carcinoma by Yun Liang, Yun Liang, Min He, Wenqing Chen, Wenqing Chen, Lizhen Li, Lizhen Li, Yumeng Dong, Yumeng Dong, Gang Liang, Hui Huangfu, Zengyu Jiang, Zengyu Jiang, Sheng He, Sheng He, Sheng He

“…BackgroundLymph node metastases (LNM) in laryngeal squamous cell carcinoma (LSCC) has been associated with lower survival, but current imaging methods, such as computed tomography (CT), have limited capabilities to identify them. …”
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Age and Saving Lives in Crisis Standards of Care: A Multicenter Cohort Study of Triage Score Prognostic Accuracy by Michael Hermsen, MD, MS, Patrick G. Lyons, MD, MS, Govind Persad, JD, PhD, Alice F. Bewley, MS, Chengsheng Mao, PhD, Kaveri Chhikara, MS, Anoop Mayampurath, PhD, Matthew Churpek, MD, PhD, Monica E. Peek, MD, MPH, MSc, Yuan Luo, PhD, William F. Parker, MD, PhD

“…IMPORTANCE:. Current protocols to triage life support use scores that are biased and inaccurate. …”
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Application of artificial intelligence in the materials science, with a special focus on fuel cells and electrolyzers by Mariah Batool, Oluwafemi Sanumi, Jasna Jankovic

“…Additionally, the review critically evaluates the current research landscape, pinpointing progress and prevailing challenges. …”
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Artificial Intelligence in Pediatric Orthopedics: A Comprehensive Review by Andrea Vescio, Gianluca Testa, Marco Sapienza, Filippo Familiari, Michele Mercurio, Giorgio Gasparini, Sergio de Salvatore, Fabrizio Donati, Federico Canavese, Vito Pavone

“…For developmental dysplasia of the hip, deep learning algorithms demonstrated high diagnostic performance in radiographic interpretation. …”
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Research advancements in the Use of artificial intelligence for prenatal diagnosis of neural tube defects by Maryam Yeganegi, Mahsa Danaei, Sepideh Azizi, Fatemeh Jayervand, Reza Bahrami, Seyed Alireza Dastgheib, Heewa Rashnavadi, Ali Masoudi, Amirmasoud Shiri, Kazem Aghili, Mahood Noorishadkam, Hossein Neamatzadeh

“…Advancements in DL algorithms, including Oct-U-Net and PAICS, have achieved recall and precision rates of 0.93 and 0.96, respectively, in identifying fetal abnormalities. …”
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Advances and challenges in immunotherapy in head and neck cancer by Hazem Aboaid, Taimur Khalid, Abbas Hussain, Yin Mon Myat, Rishi Kumar Nanda, Ramaditya Srinivasmurthy, Kevin Nguyen, Daniel Thomas Jones, Jo–Lawrence Bigcas, Kyaw Zin Thein

“…This review evaluates the current landscape of immunotherapy in both locally advanced (LA) and recurrent/metastatic (R/M) HNSCC, discussing key clinical trials, emerging biomarkers, and novel therapeutic strategies. …”
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Empowering cancer research in Europe: the EUCAIM cancer imaging infrastructure by Luis Martí-Bonmatí, Ignacio Blanquer, Manolis Tsiknakis, Gianna Tsakou, Ricard Martinez, Salvador Capella-Gutierrez, Sara Zullino, Janos Meszaros, Esther E. Bron, Jose Luis Gelpi, Katrine Riklund, Linda Chaabane, Heinz-Peter Schlemmer, Mario Aznar, Patricia Serrano Candelas, Peter Gordebeke, Monika Hierath, the EUCAIM Consortium, European Society of Radiology

“…However, the development of new AI algorithms requires access to large and complex real-world datasets. …”
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