Preoperative imaging and intraoperative navigation of the parathyroid glands neoplasms in primary hyperparathyroidism by K. Yu. Slashchuk, M. V. Degtyarev, P. O. Rumyantsev, A. K. Eremkina, N. V. Tarbaeva, D. G. Beltsevich, I. V. Kim, G. A. Melnicthhenko, N. G. Mokrysheva

“…The results allowed us to develop an algorithm for preoperative topical diagnosis of parathyroid glands in patients with laboratory-verified primary hyperparathyroidism and indications for surgical treatmen. …”
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SAHVAI‐3D and 4D: Automated AI Volumetric Measurement of Subarachnoid Hemorrhage on Noncontrast Head CT by Melina Wirtz, Saif Salman, Yujia Wei, Vishal N. Patel, Rohan Sharma, Vikash Gupta, Qiangqiang Gu, Benoit Dherin, Sanjana Reddy, Rabih G. Tawk, Bradley J. Erickson, W. David Freeman

“…The SAHVAI deep learning algorithm generated automated SAHV values in cubic centimeters. …”
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Combining Super-Resolution Imaging and Shear Wave Elastography for Enhanced Risk Assessment of Moderate-to-Severe Renal Fibrosis in Chronic Kidney Disease Patients by Huang X, Zhang Y, Hu Y, Pan J, Huang X, Zhang J, Pu H, Chen Y, Deng Q, Zhou Q

“…Furthermore, the nomogram, which integrated clinical factors and ultrasound composite parameters, exhibited excellent predictive performance (AUC = 0.878, 95% CI 0.782– 0.974). …”
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Clinical characteristics of COVID-19 in children and adolescents: insights from an Italian paediatric cohort using a machine-learning approach by Carlo Giaquinto, Daniela Paolotti, Daniele Donà, Stefania Fiandrino, Piero Poletti, Michael Davis Tira, Costanza Di Chiara

“…First, we apply an unsupervised machine-learning algorithm to cluster individuals into groups. Second, we classify new patient risk groups using a random forest classifier model based on sociodemographic information, pre-existing medical conditions, vaccination status and the VOC as predictive variables. …”
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Association of estimated glucose disposal rate with atrial fibrillation, heart failure and cardiovascular mortality in patients with diabetes: a prospective cohort study from the U... by Zhen Tan, Yijun Liu, Lei Liu, Shuang Li, Xinrui Xue, Xiaoping Li, Hongqiang Ren

“…Polygenic Risk Score (PRS) analysis evaluated the joint effects of eGDR and PRS. Boruta algorithm filtered key predictive variables. Subgroup analysis was performed using cardiovascular high-risk factors, and mediation analysis explored the relationships of eGDR with the outcomes.ResultsSubjects with higher eGDR were more likely to be female, younger, more physically active, non-smoker, and non-drinker. …”
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PDT-regulated immune gene prognostic model reveals tumor microenvironment in colorectal cancer liver metastases by Jiachi Xu, Hui Zhou, Zhongtao Liu, Yunpeng Huang, Zijian Zhang, Heng Zou, Yongxiang Wang

“…By using the weighted gene co-expression network analysis (WGCNA) algorithm, key gene modules related to metastasis in colorectal cancer were identified. …”
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Cancer epigenetics: Moving forward. by Angela Nebbioso, Francesco Paolo Tambaro, Carmela Dell'Aversana, Lucia Altucci

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Evaluation of the shielding initiative in Wales (EVITE Immunity): protocol for a quasiexperimental study by Stephen Jolles, Ashley Akbari, Andrew Carson-Stevens, Helen Snooks, Alan Watkins, Adrian Edwards, Ann John, Alison Porter, Victoria Williams, Bridie Angela Evans, Ronan Lyons, Bernadette Sewell, Mark Rhys Kingston, Tony Whiffen, Jane Lyons, Rowena Bailey, Catherine A Thornton, Lesley Bethell, Samantha Bufton, Lucy Dixon

“…Introduction Shielding aimed to protect those predicted to be at highest risk from COVID-19 and was uniquely implemented in the UK during the COVID-19 pandemic. …”
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VGGBM-Net: A Novel Pixel-Based Transfer Features Engineering for Automated Coffee Bean Diseases Classification by Muhammad Shadab Alam Hashmi, Azam Mehmood Qadri, Ali Raza, Saleem Ullah, Aseel Smerat, Changgyun Kim, Muhammad Syafrudin, Norma Latif Fitriyani

“…A novel transformation of the VGG-19 model for feature engineering based on transfer learning is introduced, where spatial features extracted from coffee bean images are transformed into class prediction probabilities using LGBM. These enhanced features are then used as inputs for advanced machine-learning algorithms. …”
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Automatic Characterization of Prostate Suspect Lesions on T2-Weighted Image Acquisitions Using Texture Features and Machine-Learning Methods: A Pilot Study by Teodora Telecan, Cosmin Caraiani, Bianca Boca, Roxana Sipos-Lascu, Laura Diosan, Zoltan Balint, Raluca Maria Hendea, Iulia Andras, Nicolae Crisan, Monica Lupsor-Platon

“…<b>Objectives</b>: We aimed to develop a machine-learning algorithm that predicts the ISUP grade of manually contoured prostate nodules on T2-weighted images and classifies them into clinically significant and indolent ones. …”
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Investigating Transcriptional Age Acceleration in Inflammatory Skin Diseases by Richie Jeremian, Melissa Galati, Rayyan Fotovati, Kaiyang Li, Carolyn Jack, David O. Croitoru, Stephan Caucheteux, Philippe Lefrançois, Vincent Piguet

“…We investigated the role of transcriptional clocks in patients with hidradenitis suppurativa (n = 37), those with atopic dermatitis (n = 27), those with plaque psoriasis (n = 28), and healthy subjects (n = 38) using 7 clock algorithms, to improve the understanding of underlying pathophysiology and disease trajectory. …”
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The Role of Landscape Metrics and Spatial Processes in Performance Evaluation of GEOMOD (Case Study: Neka River Basin) by Shrif Joorabian Shooshtari, Kamran Shayesteh, Mehdi Gholamalifard, Mahmood Azari, Juan Ignacio López-Moreno

“…In order to analyze and predict these changes, researchers have designed different types of models. …”
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An Optimal Approach for Assessing Weibull Parameters and Wind Power Potential for Six Coastal Cities in Pakistan by Ghulam Abbas, Arshad Ali, Faizan Rashid, Naveed Ashraf, Zohaib Mushtaq, Muhammad Zubair

“…In this research, we have ameliorated the performance of the recently-introduced novel energy pattern factor method (NEPFM) via a direct search algorithm, i.e., simplex search algorithm (SSA). We designate the resulting algorithm as NEPFM-SSA as it took NEPFM&#x2019;s Weibull distribution parameters as an initial guess and retuned them with the help of the simplex search algorithm to get updated Weibull distribution parameters, which ensure better fitting characteristics. …”
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A Novel Approach to Pine Nut Classification: Combining Near-Infrared Spectroscopy and Image Shape Features with Soft Voting-Based Ensemble Learning by Yueyun Yu, Xin Huang, Danjv Lv, Benjamin K. Ng, Chan-Tong Lam

“…This study proposes a novel near-infrared (NIR) spectral feature selection algorithm, termed the improved binary equilibrium optimizer with selection probability (IBiEO-SP), which incorporates a dynamic probability adjustment mechanism to achieve efficient feature dimensionality reduction. …”
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Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine by Debendra Muduli, Rani Kumari, Adnan Akhunzada, Korhan Cengiz, Santosh Kumar Sharma, Rakesh Ranjan Kumar, Dinesh Kumar Sah

“…In this MOD-POA+ELM algorithm, the modified pelican optimization algorithm (MOD-POA) has been utilized to optimize the parameters of ELM’s hidden neurons. …”
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Biomarker and clinical data–based predictor tool (MAUXI) for ultrafiltration failure and cardiovascular outcome in peritoneal dialysis patients: a retrospective and longitudinal st... by Eva María Arriero-País, María Auxiliadora Bajo-Rubio, Roberto Arrojo-García, Pilar Sandoval, Guadalupe Tirma González-Mateo, Patricia Albar-Vizcaíno, Gloria del Peso-Gilsanz, Marta Ossorio-González, Pedro Majano, Manuel López-Cabrera, Gloria del Peso-Gilsanz

“…Linear discriminant analysis (LDA) discerns among transfer to haemodialysis or death, predicts whether the cause of PD end is ultrafiltration failure (UFF) or cardiovascular disease (CVD) and anticipates the type of CVD (receiver operating characteristic curve under the area&gt;0.71).Discussion Our combination of longitudinal PD datasets, attribute shrinkage and gold-standard algorithms with overfitting testing and class imbalance ensures robust predictions in PD. …”
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Assessment of the impact of a new sequential approach to antimicrobial use in young febrile children in the emergency department (DIAFEVERCHILD): a French prospective multicentric... by Elsa Tavernier, Elise Launay, Christèle Gras Le Guen, Gaelle Hubert, Cécile Feildel Fournial, Anne Chauvire-Drouard, Fleur Lorton

“…The aims of this study are to demonstrate that using a procalcitonin (PCT) rapid test-based prediction rule (1) would not be inferior to usual practice in terms of morbidity and mortality (non-inferiority objective) and (2) would result in a significant reduction in antibiotic use (superiority objective).Methods and analysis This prospective multicentric cluster-randomised study aims to include 7245 febrile children aged 6 days to 3 years with a diagnosis of fever without source in 26 participating EDs in France and Switzerland during a 24-month period. …”
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Acceptability of Guided Symptom Entry and Asynchronous Clinical Communication Software Among Primary Care Staff: Qualitative Study by Riina Raudne, Taavi Tillmann

“…Sometimes, this arises out of the perceived mismatch between needing to identify and document critical symptom information and being unable to standardize the supply of such information, due to a heterogeneous and unpredictable communication processes whose duration, quality, and risk of miscommunication are hard to predict and control. All interviewees expressed the desire that more patients initiate their remote query via the algorithm-guided symptom-entry software. …”
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The effect of canine lingual attachments during maxillary arch distalization with clear aligner: a 4D finite element analysis and in vitro simulator study by Bochun Mao, Yajing Tian, Hanzhang Zhou, Yan Gu

“…Method A dual-methodological approach was employed: 1) A four-dimensional finite element model (4D FEM) incorporating automated staging simulation was developed, utilizing iterative computations for long-term tooth movement prediction and thermal expansion algorithms for CA morphology adaptation; 2) An electromechanical orthodontic simulator (OSIM) was implemented for in vitro validation. …”
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Neuromorphic, physics-informed spiking neural network for molecular dynamics by Vuong Van Pham, Temoor Muther, Amirmasoud Kalantari Dahaghi

“…The results indicate that NP-SNN provides a robust Sci-ML framework that can make accurate predictions across diverse scientific molecular applications. …”
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