Integrating Artificial Intelligence in dermatology: progress, challenges and perspectives by Ionela Manole, George-Sorin Tiplica

“…The ethical considerations surrounding the confidentiality of medical data, and the transparency of AI algorithms, are of utmost importance. Additionally, the availability of high-quality, annotated dermatological datasets is a limiting factor, alongside with the need for substantial technical investments and training for healthcare professionals. …”
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Revolutionizing healthcare data analytics with federated learning: A comprehensive survey of applications, systems, and future directions by Nisha Thorakkattu Madathil, Fida K. Dankar, Marton Gergely, Abdelkader Nasreddine Belkacem, Saed Alrabaee

“…Considering the healthcare domain as an example, we define the building blocks of a typical FL healthcare system, including system architecture, federation scale, data partitioning, open-source frameworks, ML models, and aggregation algorithms. Furthermore, we identify and discuss key challenges associated with the design and implementation of FL systems within the healthcare sector while outlining the directions of future research. …”
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Reduced incidence of maternal health conditions associated with the home-based newborn care intervention package in Rural Gadchiroli, India: a 13 years before – after comparison by Anand A Bang, Abhay T Bang, Rani Bang, Mahesh Deshmukh, Kalindi Soni, Sanjay Baitule

“…Based on these symptoms and signs, a computer algorithm diagnosed 20 different maternal health conditions. …”
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Muses or Stereotypes? Identifying Historical Patterns of Sexism in a Corpus of Brazilian Lyrics by Janaina Nogueira de Souza Lopes, Vitória Pereira Firmino, Valéria Quadros dos Reis

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Attention community discovery model applied to complex network information analysis by Chen Ruiwu, Liang Zeran

“…The model incorporates convolutional neural networks and spectral clustering algorithms to improve the practical application of CDMs. …”
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Machine learning prediction of metabolic dysfunction-associated fatty liver disease risk in American adults using body composition: explainable analysis based on SHapley Additive e... by Yan Hong, Xinrong Chen, Ling Wang, Fan Zhang, ZiYing Zeng, Weining Xie

“…SHapley Additive exPlanations (SHAP) were employed to interpret feature contributions.ResultsAmong the six models, the GBM algorithm exhibited the best performance, achieving area under the receiver operating characteristic curve (AUC) values of 0.875 (training) and 0.879 (validation), with minimal fluctuations in sensitivity and specificity. …”
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Development of A Novel Discharge Routing Method Based On the Large Discharge Dataset, Muskingum Model, Optimization Methods, and Multi-Criteria Decision Making by Mahdi Valikhan Anaraki, Saeed Farzin, Iman Ahmadianfar, Amin Shams

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Methodical approaches to the economic assessment of costs in the operation of cars with axial load of 27 tons at the section Kachkanar—Smychka by G. A. Granovskaya, A. I. Safonova, O. A. Suslov, N. S. Okhotnikov

“…The article describes method of calculating the coefficient reflecting the change in the impact of cars with an axial load of 27 tons on the roadbed during transportation in estimated cars compared to transportation in equivalent cars. Algorithms for calculating changes in the cost of fuel and energy costs for train traction and maintenance of the track infrastructure on the site during the operation of trains formed from cars with an axial load of 27 tons are given, as well as methods for determining the initial data for the calculation.Authors provide values of the coefficient reflecting the change in the impact of vertical and horizontal forces on the railway line when passing freight cars with an axial load of 27 tons compared to analogue cars, and the coefficient of change of the main specific resistance to motion separately for loaded and empty cars.Developed calculation algorithms and methods for obtaining baseline data allow an economic assessment of changes in infrastructure maintenance costs and fuel and energy resources for the operation of trains formed from cars with an axial load of 27 tons compared to those formed from cars with a load of 23.5 tons at the experimental section Kachkanar—Smychka.The cost change assessment carried out in 2017 shows a generally definite economic effect, while there is a reduction in costs associated with the consumption of electricity for train traction as a result of the operation of the estimated cars in the experimental section and an increase in the cost of maintaining the track superstructure and the roadbed, which is quite expected for the conditions of the organization of traffic with increased axial loads.…”
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Development and validation of a model for predicting in-hospital mortality in patients with sepsis-associated kidney injury receiving renal replacement therapy: a retrospective coh... by Caifeng Li, Ke Zhao, Qian Ren, Lin Chen, Ying Zhang, Guolin Wang, Keliang Xie

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Consensus Guidelines of Russian Society of Radiology (RSR) and Russian Association of Specialists in Ultrasound Diagnostics in Medicine (RASUDM) «Role of Imaging (X-ray, CT and US)... by V. E. Sinitsyn, I. E. Tyurin, V. V. Mitkov

“…The paper presents Consensus Guidelines of Russian Society of Radiology (RSR) and Russian Association of Specialists in Ultrasound Diagnostics in Medicine (RASUDM) «Role of imaging (X-ray, CT and US) in diagnosis of COVID-19 pneumonia» (version 2) of the Russian Society of Radiology and the Russian Association of Specialists in Ultrasound Diagnostics in Medicine.The guidelines list radiological techniques for lung diseases, which are used in coronavirus COVID-19 infection (chest X-ray, lung computed tomography (CT), and lung ultrasound (US), diagnostic algorithm, and follow-up study. …”
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Enhancing Lidar-Based 3D Classification Through an Improved Deep Learning Framework With Residual Connections by Shih-Lin Lin, Jun-Yi Wu

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AI IS LEARNING HOW TO WRITE. ETHICAL PROBLEMS FOR JOURNALISM by Dan Valeriu VOINEA

“…Key issues identified include the potential for disseminating misinformation due to AI "hallucinations," the risk of perpetuating or amplifying societal biases embedded in training data, the critical need for transparency and disclosure regarding AI authorship, complexities surrounding accountability for algorithmic outputs, and concerns about labor displacement and the changing roles of journalists. …”
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Real-world implementation and adaptation to local settings of first trimester preeclampsia screening in Italy: a systematic review by Silvia Amodeo, Giulia Bonavina, Anna Seidenari, Paolo Ivo Cavoretto, Antonio Farina

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Simplifying Field Traversing Efficiency Estimation Using Machine Learning and Geometric Field Indices by Gavriela Asiminari, Lefteris Benos, Dimitrios Kateris, Patrizia Busato, Charisios Achillas, Claus Grøn Sørensen, Simon Pearson, Dionysis Bochtis

“…This study aimed to simplify field efficiency estimation by training machine learning regression algorithms on data generated from a farm management information system covering a combination of different field areas and shapes, working patterns, and machine-related parameters. …”
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Novel bacterial cluster “Prevotella, Bacteroides and Suterella” associated with mortality in Mexican patients with acute-on-chronic liver failure (ACLF) and clinical utility of sys... by Paula A. Castaño Jiménez, Tonatiuh A. Baltazar-Díaz, Rodrigo Hernández-Basulto, Mayra P. Padilla-Sánchez, Ksenia K. Kravtchenko, Roxana García-Salcido, María T. Tapia-De la paz, Kevin J. Arellano-Arteaga, Luz A. González-Hernández, Miriam R. Bueno-Topete

“…Quality filtering, which includes removal of chimeras and non-biological sequences, was performed using the DADA2 algorithm. Resulting ASVs were taxonomically assigned through a self-trained naïve Bayesian classifier, against the SILVA database. …”
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Single-Stage Entity–Relation Joint Extraction of Pesticide Registration Information Based on HT-BES Multi-Dimensional Labeling Strategy by Chenyang Dong, Shiyu Xi, Yinchao Che, Shufeng Xiong, Xinming Ma, Lei Xi, Shuping Xiong

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Among Artificial Intelligence/Machine Learning Methods, Automated Gradient-Boosting Models Accurately Score Intraoral Plaque in Non-Standardized Images by Eric Coy, William Santo, Bonnie Jue, Helen Betts, Francisco Ramos-Gomez, Stuart A. Gansky

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Using Machine Learning to Predict Outcomes Following Transfemoral Carotid Artery Stenting by Ben Li, Naomi Eisenberg, Derek Beaton, Douglas S. Lee, Leen Al‐Omran, Duminda N. Wijeysundera, Mohamad A. Hussain, Ori D. Rotstein, Charles de Mestral, Muhammad Mamdani, Graham Roche‐Nagle, Mohammed Al‐Omran

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Detection of Right and Left Ventricular Dysfunction in Pediatric Patients Using Artificial Intelligence–Enabled ECGs by Scott Anjewierden, Donnchadh O'Sullivan, Kathryn E. Mangold, Grace Greason, Itzhak Zachi Attia, Francisco Lopez‐Jimenez, Paul A. Friedman, Samuel J. Asirvatham, Jason Anderson, Benjamin W. Eidem, Jonathan N. Johnson, Shisheer Havangi Prakash, Talha Niaz, Malini Madhavan

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Using Machine Learning to Predict Outcomes Following Thoracic and Complex Endovascular Aortic Aneurysm Repair by Ben Li, Naomi Eisenberg, Derek Beaton, Douglas S. Lee, Badr Aljabri, Leen Al‐Omran, Duminda N. Wijeysundera, Ori D. Rotstein, Thomas F. Lindsay, Charles de Mestral, Muhammad Mamdani, Graham Roche‐Nagle, Mohammed Al‐Omran

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